Triple
T120563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boston Marathon |
E2435
|
entity |
| Predicate | firstOfficialWomenRace |
P1161
|
FINISHED |
| Object | 1972 |
—
|
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: 1972 | Statement: [Boston Marathon, firstOfficialWomenRace, 1972]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstOfficialWomenRace Context triple: [Boston Marathon, firstOfficialWomenRace, 1972]
-
A.
isFirstFemaleHolderOfOffice
Indicates that a person is the first woman ever to hold a particular office or position.
-
B.
firstOfficialClaimBy
Indicates that an entity is the earliest or original official source to assert or make a particular claim.
-
C.
firstCelebratedInYear
chosen
Indicates the year in which something (such as an event, holiday, or celebration) was first observed or celebrated.
-
D.
firstAwarded
Indicates the time or occasion when an award, honor, or recognition was given for the very first time.
-
E.
firstInOfficeTo
Indicates that one entity was the earliest or first to hold a particular office or position in relation to another 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a258fd278481908ad4498e03f38e2f |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a25647fe6081908cb0405266d35ff5 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.