Triple
T10763339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese transport Kowshing |
E253887
|
entity |
| Predicate | legalStatusAtTimeOfSinking |
P95857
|
FINISHED |
| Object | neutral merchant vessel under British flag |
—
|
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: neutral merchant vessel under British flag | Statement: [Chinese transport Kowshing, legalStatusAtTimeOfSinking, neutral merchant vessel under British flag]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusAtTimeOfSinking Context triple: [Chinese transport Kowshing, legalStatusAtTimeOfSinking, neutral merchant vessel under British flag]
-
A.
missionAtTimeOfSinking
Indicates that a vessel was engaged in a specific mission or operational role at the time it sank.
-
B.
constructionStatusAtSinking
Indicates the stage or condition of a structure’s construction at the time it sank.
-
C.
dateOfSinking
Indicates the specific calendar date on which an entity (typically a vessel or structure) sank.
-
D.
placeOfSinking
Indicates the location where an object or entity sank or was submerged.
-
E.
captainAtTimeOfSinking
Indicates that the subject was serving as the ship’s captain at the specific time when the ship sank.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d731a373708190ae5ac0c027a4014c |
completed | April 9, 2026, 4:57 a.m. |
| PD | Predicate disambiguation | batch_69d6f311529c819080ca5493d55d6050 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa323564819097b207eb53f8a9b8 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:16 p.m.