Triple
T2970328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RMS Titanic |
E80262
|
entity |
| Predicate | totalPersonsOnBoard |
P2307
|
FINISHED |
| Object | about 2224 |
—
|
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 2224 | Statement: [RMS Titanic, totalPersonsOnBoard, about 2224]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalPersonsOnBoard Context triple: [RMS Titanic, totalPersonsOnBoard, about 2224]
-
A.
totalPeopleOnBoard
Indicates the total number of people currently present on a given vehicle, vessel, or similar conveyance.
-
B.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
C.
crewCount
Indicates the number of crew members associated with an entity, such as a vehicle, vessel, or mission.
-
D.
numberOfPersons
chosen
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
-
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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad997282b481909d078be0e70d9930 |
completed | March 8, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69ad960e71f8819088179d11248c6ed0 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:58 p.m.