Triple
T6423145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Triangle Shirtwaist Factory fire |
E127992
|
entity |
| Predicate | oldestVictimAge |
P70790
|
FINISHED |
| Object | 43 |
—
|
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: 43 | Statement: [Triangle Shirtwaist Factory fire, oldestVictimAge, 43]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oldestVictimAge Context triple: [Triangle Shirtwaist Factory fire, oldestVictimAge, 43]
-
A.
victimAge
Indicates the age of the person who is the victim in the described event or situation.
-
B.
isEarliestAgeOf
Indicates that one value represents the minimum or first age at which a specified condition, event, or state occurs for an entity.
-
C.
typicallyIssuedAtAge
Indicates the age at which something is most commonly or customarily issued to an individual.
-
D.
isYoungestOf
Indicates that the subject is the youngest member within the specified group or set of related entities.
-
E.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
- 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_69c00838de888190af2eec0b80495efa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0690576c48190b5db5464eacc9de3 |
completed | March 22, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69c060f780b08190aa650b4d1fc51f21 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c062d290448190a2183158ef75d129 |
completed | March 22, 2026, 9:44 p.m. |
Created at: March 22, 2026, 4:43 p.m.