Triple
T33331956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lope de Aguirre |
E853428
|
entity |
| Predicate | declaredAllegiance |
P110386
|
FINISHED |
| Object | King Philip II of Spain’s enemies |
—
|
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: King Philip II of Spain’s enemies | Statement: [Lope de Aguirre, declaredAllegiance, King Philip II of Spain’s enemies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: declaredAllegiance Context triple: [Lope de Aguirre, declaredAllegiance, King Philip II of Spain’s enemies]
-
A.
hadAllegiance
Indicates that an entity was loyally committed or formally bound in support or service to another entity, such as a person, group, or cause.
-
B.
stateAllegiance
chosen
Indicates that one entity formally declares loyalty or support to another entity, such as a person, group, or state.
-
C.
namedForAllegiance
Indicates that an entity is named in reference to, or in honor of, a particular allegiance, affiliation, or loyalty.
-
D.
allegiance
Indicates a relationship where one entity is loyal, committed, or obligated in support or service to another entity.
-
E.
countryOfAllegiance
Indicates the country to which an entity owes loyalty, support, or official allegiance.
- 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_69f34969614c81909cd99661b0902533 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e3156ea48190b604e414665ef351 |
completed | May 3, 2026, 5:54 a.m. |
| PD | Predicate disambiguation | batch_69f6de0b9ba48190887c9eb5d06a2e94 |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:34 a.m.