Triple
T33030097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guillaume d’Orange |
E845140
|
entity |
| Predicate | mainAdversaries |
P68850
|
FINISHED |
| Object | Saracens |
—
|
NE NERFINISHED |
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: Saracens | Statement: [Guillaume d’Orange, mainAdversaries, Saracens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainAdversaries Context triple: [Guillaume d’Orange, mainAdversaries, Saracens]
-
A.
otherAdversary
Indicates that one entity is an adversary of another, distinct from any primary or previously identified adversary.
-
B.
primaryAntagonists
Indicates that the referenced entities serve as the main opposing or adversarial forces in relation to a specified subject or narrative.
-
C.
primaryAdversaryImplied
Indicates that an entity is understood or suggested, rather than explicitly stated, to be the main opponent or chief adversary of another entity.
-
D.
primaryAdversaryContext
Indicates the main opposing force or conflict-driving element that defines the central adversarial situation within a given context.
-
E.
hasMainAdversary
chosen
Indicates that an entity’s primary or most significant opponent, rival, or enemy is another specified entity.
- F. None of above.
Provenance (3 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_69f34950749c8190ae05cd27adb16d58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f70b966860819089cf92927f47c5f1 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70abe43e08190b2a30930d96247c1 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:24 a.m.