Triple
T26931389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alfonso Herrera Salcedo |
E678231
|
entity |
| Predicate | roleInNappilyEverAfter |
P191081
|
FINISHED |
| Object | cinematographer |
—
|
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: cinematographer | Statement: [Alfonso Herrera Salcedo, roleInNappilyEverAfter, cinematographer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInNappilyEverAfter Context triple: [Alfonso Herrera Salcedo, roleInNappilyEverAfter, cinematographer]
-
A.
roleInTangled
Indicates that an entity has a specific role or function within the context of "Tangled" (e.g., the film, story, or related production).
-
B.
roleInShrekForeverAfter
Indicates that an entity has a specific acting or production role in the movie "Shrek Forever After."
-
C.
roleInStories
Indicates the specific function, position, or character part an entity plays within one or more stories.
-
D.
roleInTheWay
Indicates that one entity is obstructing, hindering, or otherwise blocking another entity’s progress, action, or intended path.
-
E.
roleInMulan
Indicates that one entity has a specific role or part in the context of "Mulan" (such as the film, story, or production).
- 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_69eeeb4cac908190a45956c2993d1cc2 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69fcda3699948190adb57625bae08091 |
completed | May 7, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fd16d08190b0aca6e19a632e99 |
completed | May 7, 2026, 6:25 p.m. |
| PDg | Predicate description generation | batch_69fcda35dc048190a3c90e15230900e0 |
completed | May 7, 2026, 6:30 p.m. |
Created at: April 27, 2026, 6:12 a.m.