Triple
T32190285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lieutenant Ilia |
E822218
|
entity |
| Predicate | hasRankAtTimeOfFilm |
P187587
|
FINISHED |
| Object | Lieutenant, junior grade |
—
|
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: Lieutenant, junior grade | Statement: [Lieutenant Ilia, hasRankAtTimeOfFilm, Lieutenant, junior grade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankAtTimeOfFilm Context triple: [Lieutenant Ilia, hasRankAtTimeOfFilm, Lieutenant, junior grade]
-
A.
hasFilmScoreBy
Indicates that a film’s musical score was composed or created by a specified person or entity.
-
B.
eligibilityYearOfFilm
Indicates the specific year in which a film qualifies or is considered eligible for a particular award, category, or recognition.
-
C.
hasFilmScore
Indicates that one entity serves as the musical score or soundtrack composed for a particular film.
-
D.
associatedWithReleaseDateOfFilm
Indicates a relationship where something is connected to or corresponds with the release date of a film.
-
E.
ageInFirstFilm
Indicates the age a person was when they appeared in their first film.
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
| PDg | Predicate description generation | batch_69fb6fdab95c81909acff3c6a2359787 |
completed | May 6, 2026, 4:44 p.m. |
Created at: May 1, 2026, 12:35 a.m.