Triple
T957313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Frost |
E20652
|
entity |
| Predicate | numberOfPulitzerPrizes |
P3160
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Robert Frost, numberOfPulitzerPrizes, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPulitzerPrizes Context triple: [Robert Frost, numberOfPulitzerPrizes, 4]
-
A.
numberOfAwards
chosen
Indicates the total count of awards that have been received by an entity.
-
B.
dateAwarded Pulitzer Prize for Fiction
Indicates that a specific date is when an entity received the Pulitzer Prize for Fiction.
-
C.
hasLaureate
Indicates that an entity (such as an award or prize) has a specific person or group as its laureate or recipient.
-
D.
nobelPrizeRelated
Indicates that there is a connection or association between an entity and the Nobel Prize, such as receiving, being nominated for, or otherwise being significantly linked to it.
-
E.
typicalNumberOfLaureatesPerYear
Indicates the usual or average number of laureates associated with a given award or context in a single year.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3fac2bc8190a66feb70c68899b2 |
completed | March 1, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a18ecc8190883f6206fe3b0fb6 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.