Triple
T31324382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French frigate Méduse |
E798840
|
entity |
| Predicate | timeAdriftOnRaft |
P171247
|
FINISHED |
| Object | 13 days |
—
|
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: 13 days | Statement: [French frigate Méduse, timeAdriftOnRaft, 13 days]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeAdriftOnRaft Context triple: [French frigate Méduse, timeAdriftOnRaft, 13 days]
-
A.
survivesShipwreck
Indicates that an entity continues to live or remain alive after experiencing a shipwreck.
-
B.
travelTimeByBoat
Indicates the amount of time it takes to travel between two locations specifically when using a boat as the mode of transportation.
-
C.
lifeboatDuration
Indicates the length of time a lifeboat can support occupants or remain operational under specified conditions.
-
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.
hasRaftingDifficulty
Indicates that an entity is associated with a specific level of rafting difficulty.
- 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_69f224e3238c8190b2291f50ea4962cd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f11ba548190b8ad25fafb07b62b |
completed | May 3, 2026, 1:04 a.m. |
| PD | Predicate disambiguation | batch_69f69d1d25e88190a7f57d323574da90 |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69ea761848190acb31298e65b7892 |
completed | May 3, 2026, 1:02 a.m. |
Created at: April 29, 2026, 9:15 p.m.