Triple
T36196818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Bainbridge (DD-1) |
E1047149
|
entity |
| Predicate | assignedTheater |
P137954
|
FINISHED |
| Object | Philippine waters |
—
|
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: Philippine waters | Statement: [USS Bainbridge (DD-1), assignedTheater, Philippine waters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: assignedTheater Context triple: [USS Bainbridge (DD-1), assignedTheater, Philippine waters]
-
A.
intendedTheater
Indicates the theater or venue that an event, performance, or screening is planned or meant to take place in.
-
B.
theaterAssignment
chosen
Indicates that an entity is assigned to a particular theater or performance venue for an event, show, or activity.
-
C.
belongsToTheatre
Indicates that something is a member, part, or property of a particular theatre or theatre organization.
-
D.
plannedTheater
Indicates that an entity has scheduled or arranged for a theater-related event or activity to take place.
-
E.
locatedInTheater
Indicates that something is situated within or inside a theater.
- 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_69f76e414bdc8190996f15a544220a3d |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b69b333081909cadbed3fcb8ecf5 |
completed | May 3, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c2a5f8819094ad4621d7b97e0c |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:08 p.m.