Triple
T1381889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NI |
E29355
|
entity |
| Predicate | hasInitialLetters |
P27166
|
FINISHED |
| Object | N |
—
|
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: N | Statement: [NI, hasInitialLetters, N]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInitialLetters Context triple: [NI, hasInitialLetters, N]
-
A.
hasLetter
Indicates that one entity contains, includes, or is associated with a specific letter or character.
-
B.
hasAdditionalLetters
Indicates that one entity contains extra or more letters than another entity, beyond a specified base set or reference.
-
C.
hasBasicLetters
Indicates that an entity contains or is composed of fundamental alphabetic characters, without additional symbols or diacritics.
-
D.
hasNumberOfLetters
Indicates a relationship where an entity is associated with the count of letters it contains.
-
E.
hasInitial
Indicates that one entity possesses or is associated with the first letter or starting character of another entity’s name or value.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c31b176c8190a896183140c5c8be |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4befe343c81909f758440a531b5be |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c0335f7081908d50046ced4cdee0 |
completed | March 1, 2026, 10:39 p.m. |
Created at: March 1, 2026, 7:59 p.m.