Triple
T5008061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hi5 |
E112544
|
entity |
| Predicate | acquiredBy |
P347
|
FINISHED |
| Object |
Tagged
Tagged is a social networking service known for its focus on meeting new people through social discovery features like games, profiles, and friend suggestions.
|
E487084
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tagged | Statement: [Hi5, acquiredBy, Tagged]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tagged Context triple: [Hi5, acquiredBy, Tagged]
-
A.
TAG
TAG is the W3C Technical Architecture Group, a committee that steers the architectural principles and long-term technical direction of the World Wide Web.
-
B.
Tok
Tok is a small unincorporated community in eastern Alaska, known as a gateway to the state for travelers on the Alaska Highway.
-
C.
Hung
Hung is an American comedy-drama television series that aired on HBO, following a struggling high school coach who turns to an unusual side job to make ends meet.
-
D.
EZ TAG
EZ TAG is an electronic toll collection system used on certain Texas toll roads that allows drivers to pay tolls automatically without stopping.
-
E.
Last Seen Wearing
"Last Seen Wearing" is a crime novel in Colin Dexter's Inspector Morse series, featuring the detective's investigation into the disappearance of a schoolgirl.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tagged Triple: [Hi5, acquiredBy, Tagged]
Generated description
Tagged is a social networking service known for its focus on meeting new people through social discovery features like games, profiles, and friend suggestions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tagged Target entity description: Tagged is a social networking service known for its focus on meeting new people through social discovery features like games, profiles, and friend suggestions.
-
A.
TAG
TAG is the W3C Technical Architecture Group, a committee that steers the architectural principles and long-term technical direction of the World Wide Web.
-
B.
Tok
Tok is a small unincorporated community in eastern Alaska, known as a gateway to the state for travelers on the Alaska Highway.
-
C.
Hung
Hung is an American comedy-drama television series that aired on HBO, following a struggling high school coach who turns to an unusual side job to make ends meet.
-
D.
EZ TAG
EZ TAG is an electronic toll collection system used on certain Texas toll roads that allows drivers to pay tolls automatically without stopping.
-
E.
Last Seen Wearing
"Last Seen Wearing" is a crime novel in Colin Dexter's Inspector Morse series, featuring the detective's investigation into the disappearance of a schoolgirl.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd72eb05f881908d7dc3d7cd07b2ae |
completed | March 20, 2026, 4:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9266314881909dfb710c5b5c8f65 |
completed | March 21, 2026, 12:43 p.m. |
| NEDg | Description generation | batch_69be93cfbe2881908cf97dd9ec5d28b5 |
completed | March 21, 2026, 12:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69be9448b5148190903775d394a095f0 |
completed | March 21, 2026, 12:51 p.m. |
Created at: March 20, 2026, 1:35 p.m.