Triple
T30034483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippine–United States relations |
E763115
|
entity |
| Predicate | hasTensionsOver |
P61068
|
FINISHED |
| Object | military base presence |
—
|
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: military base presence | Statement: [Philippine–United States relations, hasTensionsOver, military base presence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTensionsOver Context triple: [Philippine–United States relations, hasTensionsOver, military base presence]
-
A.
hasTypeOfTension
Indicates that one entity is associated with, or characterized by, a specific kind or category of tension.
-
B.
hasTension
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
C.
diplomaticTensionBetween
Indicates a strained or conflict-prone diplomatic relationship existing between two entities.
-
D.
hasCauseOfConflict
chosen
Indicates a relationship where one entity is the source or reason for a conflict involving another entity.
-
E.
hasEthnicTensionHistory
Indicates that there has been a history of conflict, strain, or hostility between ethnic groups within the referenced context.
- 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_69f2246fb2b88190acff36bf7975c8f0 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
Created at: April 29, 2026, 6:50 p.m.