Triple
T11759751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Thomas Shoal |
E279621
|
entity |
| Predicate | garrisonVesselType |
P17521
|
FINISHED |
| Object | Philippine Navy ship intentionally grounded |
—
|
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 Navy ship intentionally grounded | Statement: [Second Thomas Shoal, garrisonVesselType, Philippine Navy ship intentionally grounded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: garrisonVesselType Context triple: [Second Thomas Shoal, garrisonVesselType, Philippine Navy ship intentionally grounded]
-
A.
navalStandardType
Indicates the specific naval standard or classification system under which an entity (such as a vessel, equipment, or procedure) is defined or regulated.
-
B.
governmentVessel
Indicates that the vessel is owned, operated, or officially designated for use by a government or governmental authority.
-
C.
garrisonType
chosen
Indicates the specific kind or classification of military garrison associated with an entity.
-
D.
shipTypeProduced
Indicates that a particular type of ship is produced, built, or manufactured by a given entity.
-
E.
shipClass
Indicates the classification or type category to which a particular ship belongs.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a5220f148190ae60d1941a579ab6 |
completed | April 10, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69d88a829fe481909cc5431de7d6058e |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.