Triple
T19263978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1999 Martha's Vineyard plane crash |
E481721
|
entity |
| Predicate | overWater |
P135335
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [1999 Martha's Vineyard plane crash, overWater, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: overWater Context triple: [1999 Martha's Vineyard plane crash, overWater, true]
-
A.
acrossWaterFrom
Indicates that two entities are located on opposite sides of a body of water, separated by that water.
-
B.
hasWatersOf
Indicates that a geographic or physical entity contains, is traversed by, or is otherwise characterized by specific bodies or types of water.
-
C.
surfaceWater
Indicates that one entity consists of or contains surface-level water associated with another entity.
-
D.
tookOnWater
Indicates that an entity began to fill or absorb water, typically in an unintended or problematic way (e.g., a vessel leaking or flooding).
-
E.
bodyOfWaterOnOtherSide
Indicates that one entity is located across a body of water from the other entity, with the water lying between them.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb8bce6881908395836960762672 |
completed | April 20, 2026, 10:10 a.m. |
| PD | Predicate disambiguation | batch_69e4dd07a7208190afcd51ba1dc87c33 |
completed | April 19, 2026, 1:47 p.m. |
| PDg | Predicate description generation | batch_69e4df51ac6c819091ce72b07790ffa6 |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 1:28 p.m.