Triple
T35966500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Daniel J. Morrell shipwreck |
E1040155
|
entity |
| Predicate | crewComplementApprox |
P883
|
FINISHED |
| Object | about 29 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: about 29 crew members | Statement: [SS Daniel J. Morrell shipwreck, crewComplementApprox, about 29 crew members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewComplementApprox Context triple: [SS Daniel J. Morrell shipwreck, crewComplementApprox, about 29 crew members]
-
A.
crewComplementType
Indicates the classification or category of a crew complement associated with an entity (such as its role, composition, or staffing type).
-
B.
crewCountApproximate
chosen
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
C.
crewOnboard
Indicates that a person or group is serving as crew aboard a specific vehicle, vessel, or craft.
-
D.
crewCount
Indicates the number of crew members associated with an entity, such as a vehicle, vessel, or mission.
-
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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.