Triple
T415397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treasure Island |
E9580
|
entity |
| Predicate | militaryUseStart |
P3656
|
FINISHED |
| Object | 1941 |
—
|
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: 1941 | Statement: [Treasure Island, militaryUseStart, 1941]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryUseStart Context triple: [Treasure Island, militaryUseStart, 1941]
-
A.
locationOfFirstCommercialUse
Indicates the place where something was first used commercially.
-
B.
militaryContext
Indicates that the relationship or action occurs within a military setting, framework, or operational environment.
-
C.
historicalPeriodOfUse
chosen
Indicates the time period during which something was in active use or commonly utilized.
-
D.
militaryTechnology
Indicates that one entity is a type of military-related technology used for defense, combat, or warfare purposes.
-
E.
beganCivilOperations
Indicates that an entity initiated or commenced civil (non-military) administrative or operational activities in relation to another entity or 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eebde1d881908fb212bfba9d7c67 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edcff4688190809d83d112ff25a5 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:09 p.m.