Triple
T14806510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry, He’s Here to Help |
E348050
|
entity |
| Predicate | hasStrangerCharacter |
P115802
|
FINISHED |
| Object | yes |
—
|
LITERAL FINISHED |
How this triple was built (2 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: yes | Statement: [Harry, He’s Here to Help, hasStrangerCharacter, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStrangerCharacter Context triple: [Harry, He’s Here to Help, hasStrangerCharacter, yes]
-
A.
hasEnigmaticCharacter
Indicates that something possesses a mysterious, puzzling, or difficult-to-interpret quality or nature.
-
B.
hasGhostCharacter
Indicates that an entity includes, features, or is associated with a character that is a ghost.
-
C.
hasStrangeness
Indicates that an entity possesses a specified value of the quantum property known as strangeness.
-
D.
hasThiefCharacter
Indicates that an entity includes or features a character whose role or identity is that of a thief.
-
E.
hasCharacters
Indicates that an entity (such as a work or story) includes or features certain characters as part of its content.
- F. None of above. chosen
Provenance (4 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decf33b6a08190ab6a4cfeda2cc09c |
completed | April 14, 2026, 11:35 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:40 a.m.