Triple
T30373139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarakan operation |
E772604
|
entity |
| Predicate | forceStrengthJapanese |
P37795
|
FINISHED |
| Object | approximately 2,000–2,500 personnel |
—
|
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: approximately 2,000–2,500 personnel | Statement: [Tarakan operation, forceStrengthJapanese, approximately 2,000–2,500 personnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: forceStrengthJapanese Context triple: [Tarakan operation, forceStrengthJapanese, approximately 2,000–2,500 personnel]
-
A.
JapaneseForceStrength
chosen
Indicates the size or magnitude of the Japanese military forces involved in a particular context or operation.
-
B.
JapaneseForceType
Indicates that an entity is classified as a type of Japanese military or armed force.
-
C.
JapaneseForceName
Indicates that an entity is known by a name used for a Japanese military or armed force.
-
D.
JapaneseFormation
Indicates a relationship where something is formed, created, or organized according to Japanese style, methods, or origin.
-
E.
JapaneseUnit
Indicates that an entity is a unit of measurement or organization that is specific to or used within Japan.
- 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_69f2248d71408190aec0d5c2001b1cff |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6828532d081909897bbe49b280ced |
completed | May 2, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 7:59 p.m.