Triple
T3066911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hector Barbossa |
E62123
|
entity |
| Predicate | statusAfterFirstFilm |
P44210
|
FINISHED |
| Object | resurrected |
—
|
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: resurrected | Statement: [Hector Barbossa, statusAfterFirstFilm, resurrected]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusAfterFirstFilm Context triple: [Hector Barbossa, statusAfterFirstFilm, resurrected]
-
A.
protagonistStatusAfterSleep
Indicates the condition or state of the main character immediately following a period of sleep.
-
B.
firstSawAction
Indicates that one entity was the earliest or initial observer of a particular action performed by another entity.
-
C.
statusAfter1996
Indicates the status or condition of an entity as it exists after the year 1996.
-
D.
protagonistAgeRelativeToPrequel
Indicates how the protagonist’s age in the current work compares to their age in a preceding prequel story.
-
E.
firstAVA
Indicates that the subject is the first entity (e.g., version, appearance, or instance) in a sequence associated with the object.
- 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada0fd87308190918e7b616f033faa |
completed | March 8, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69ad9624b7a0819091d255614f5819ea |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f7630c81908e1ca8a69611cff6 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 3:02 p.m.