Triple
T2229214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Hudson set adrift |
E48724
|
entity |
| Predicate | hasOpposingSide |
P36358
|
FINISHED |
| Object | mutinous crew |
—
|
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: mutinous crew | Statement: [John Hudson set adrift, hasOpposingSide, mutinous crew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpposingSide Context triple: [John Hudson set adrift, hasOpposingSide, mutinous crew]
-
A.
hasOpposingFront
Indicates that one entity’s front side is directly facing or oriented opposite to the front side of another entity.
-
B.
hasOpposingForceType
Indicates that one force is characterized as being of a type that opposes or counteracts another force.
-
C.
hasOpposingAlliance
Indicates that two entities belong to alliances or factions that are in direct opposition or conflict with each other.
-
D.
hasMainOpposition
Indicates that one entity serves as the primary opposing force, rival, or counterparty to another entity.
-
E.
hasOppositionParties
Indicates that an entity (typically a government or ruling body) has one or more political parties that formally oppose or challenge its policies or authority.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0685b688190857a76c1043f4b92 |
completed | March 7, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69abbdadbb0c8190b3a1ede31b8acbfa |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbe4252688190944491a450383450 |
completed | March 7, 2026, 5:57 a.m. |
Created at: March 4, 2026, 7:47 p.m.