Triple
T3908552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inchon Regiment |
E87265
|
entity |
| Predicate | roleInBattleOfInchon |
P28183
|
FINISHED |
| Object | pivotal role in amphibious landing |
—
|
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: pivotal role in amphibious landing | Statement: [Inchon Regiment, roleInBattleOfInchon, pivotal role in amphibious landing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInBattleOfInchon Context triple: [Inchon Regiment, roleInBattleOfInchon, pivotal role in amphibious landing]
-
A.
roleInKoreanWar
Indicates the specific function, position, or involvement an entity had during the Korean War.
-
B.
militaryRole
Indicates the specific function, position, or duty an entity holds within a military organization or context.
-
C.
roleInManchuria
Indicates that an entity holds or held a specific role, position, or function in the context of Manchuria.
-
D.
notableBattleRole
chosen
Indicates the specific role or function an entity played in a notable or historically significant battle.
-
E.
servedInRole
Indicates that one entity performed duties or held a position within a specified role or office in relation to another 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75cff148190b6d5979d17fae085 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.