Triple
T30965777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Celeste |
E788952
|
entity |
| Predicate | crewCountOnFinalVoyage |
P30694
|
FINISHED |
| Object | 7 crew members |
—
|
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: 7 crew members | Statement: [Mary Celeste, crewCountOnFinalVoyage, 7 crew members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewCountOnFinalVoyage Context triple: [Mary Celeste, crewCountOnFinalVoyage, 7 crew members]
-
A.
crewCount
chosen
Indicates the number of crew members associated with an entity, such as a vehicle, vessel, or mission.
-
B.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
C.
crewAndPassengersCount
Indicates the total number of people on a vehicle or vessel, combining both crew members and passengers.
-
D.
statusDuringFinalVoyage
Indicates the role, condition, or state an entity held specifically during its final voyage.
-
E.
totalCrewMembers
Indicates the total number of crew members associated with a given entity or context.
- 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_69f224c3a6b48190951add9b7b7f0271 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:54 p.m.