Triple
T5782921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toby |
E128202
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object |
Tobi
Tobi is a given name, often used as a variant of Toby, that can be used for people of any gender in various cultures.
|
E543518
|
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: Tobi | Statement: [Toby, hasVariantSpelling, Tobi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tobi Context triple: [Toby, hasVariantSpelling, Tobi]
-
A.
Tio
Tio is a coastal town in Eritrea’s Southern Red Sea Region, known historically as a small port on the Red Sea.
-
B.
Nagato
Nagato was a famous Japanese battleship of the Imperial Japanese Navy, notable for serving as Admiral Yamamoto’s flagship during the attack on Pearl Harbor and later participating in major World War II engagements.
-
C.
Obi
Obi is a local government area and town in Benue State, Nigeria, traditionally associated with and inhabited by the Idoma people.
-
D.
Obi
Obi is a local government area in Nasarawa State, Nigeria, serving as an administrative subdivision of the state.
-
E.
Toby
Toby is a central protagonist in Margaret Atwood’s dystopian MaddAddam trilogy, known for her resilience, survival skills, and complex moral perspective in a post-apocalyptic world.
- 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: Tobi Triple: [Toby, hasVariantSpelling, Tobi]
Generated description
Tobi is a given name, often used as a variant of Toby, that can be used for people of any gender in various cultures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tobi Target entity description: Tobi is a given name, often used as a variant of Toby, that can be used for people of any gender in various cultures.
-
A.
Tio
Tio is a coastal town in Eritrea’s Southern Red Sea Region, known historically as a small port on the Red Sea.
-
B.
Nagato
Nagato was a famous Japanese battleship of the Imperial Japanese Navy, notable for serving as Admiral Yamamoto’s flagship during the attack on Pearl Harbor and later participating in major World War II engagements.
-
C.
Obi
Obi is a local government area and town in Benue State, Nigeria, traditionally associated with and inhabited by the Idoma people.
-
D.
Obi
Obi is a local government area in Nasarawa State, Nigeria, serving as an administrative subdivision of the state.
-
E.
Toby
Toby is one of the central sailor protagonists in Herman Melville’s semi-autobiographical novel "Typee," known for his role in the narrative of escape and survival among a Polynesian tribe.
- 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_69c0084450048190bc647b649a05136b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a184870819084251554eae1e33c |
completed | March 22, 2026, 5:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e7a1cb88190980e0cf675aaa906 |
completed | March 22, 2026, 11:42 p.m. |
| NEDg | Description generation | batch_69c086b2f5888190a986efaf948b25fb |
completed | March 23, 2026, 12:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c087493f808190bec82872e44af85c |
completed | March 23, 2026, 12:20 a.m. |
Created at: March 22, 2026, 3:50 p.m.