Triple
T5989585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS San Francisco (CA-38) |
E133310
|
entity |
| Predicate | battleStars |
P67776
|
FINISHED |
| Object | 17 battle stars |
—
|
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: 17 battle stars | Statement: [USS San Francisco (CA-38), battleStars, 17 battle stars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: battleStars Context triple: [USS San Francisco (CA-38), battleStars, 17 battle stars]
-
A.
battleAlsoKnownAs
Indicates that a particular battle is known by an alternative name or names.
-
B.
battlePartOf
Indicates that a specific battle is a component or segment of a larger military campaign, war, or conflict.
-
C.
battleDepicted
Indicates that a work or representation visually portrays a specific battle or combat event.
-
D.
battleWasPartOf
Indicates that a specific battle occurred as a component or phase within a larger military campaign, war, or conflict.
-
E.
flagshipDuringBattle
Indicates that one entity serves as the primary command ship for another entity during a specific battle or military engagement.
- F. None of above. chosen
Provenance (4 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc76fd481908cc3f327e532a1a6 |
completed | March 22, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69c049de98648190962b14fd341c93da |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04a663a4481908983048c69cba6b6 |
completed | March 22, 2026, 8 p.m. |
Created at: March 22, 2026, 4:05 p.m.