Triple
T32304089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Franco |
E825312
|
entity |
| Predicate | roleInBoycott |
P201763
|
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: [David Franco, roleInBoycott, cinematographer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInBoycott Context triple: [David Franco, roleInBoycott, cinematographer]
-
A.
reasonForBoycott
Indicates that one entity is the cause, motive, or justification for another entity’s decision to initiate or participate in a boycott.
-
B.
boycottType
Indicates the specific category or form of boycott involved in the relationship or action.
-
C.
boycottSupportedBy
Indicates that a boycott is endorsed, backed, or actively supported by a particular party or group.
-
D.
boycottingNation
Indicates that one nation is refusing to engage in normal relations, trade, or cooperation with another nation as an act of protest or pressure.
-
E.
boycottOccurredIn
Indicates that a boycott event took place within a specific location or geopolitical area.
- 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_69f349115304819084ee91d345b6c8aa |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a001cc0ff588190bb7c8a6fd427d02b |
completed | May 10, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_6a001b3ea18c8190aeda7a32b2697490 |
completed | May 10, 2026, 5:44 a.m. |
| PDg | Predicate description generation | batch_6a001cc053ac8190927768a4ecb023b9 |
completed | May 10, 2026, 5:50 a.m. |
Created at: May 1, 2026, 12:45 a.m.