Triple
T12364723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1868 United States presidential election |
E294830
|
entity |
| Predicate | tookPlaceInNumberOfStates |
P14077
|
FINISHED |
| Object | 37 |
—
|
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: 37 | Statement: [1868 United States presidential election, tookPlaceInNumberOfStates, 37]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookPlaceInNumberOfStates Context triple: [1868 United States presidential election, tookPlaceInNumberOfStates, 37]
-
A.
numberOfStates
Indicates the total count of distinct states or conditions associated with an entity or system.
-
B.
spansStates
Indicates that something extends across or covers multiple states or state-level jurisdictions.
-
C.
hasNumberOfStatesAndDistricts
Indicates a relationship where an entity is associated with a specific count of its constituent states and districts.
-
D.
numberOfStatesRepresented
chosen
Indicates how many distinct states are represented or covered in a given context or entity.
-
E.
states
Indicates that an entity formally declares, expresses, or asserts a fact, opinion, or condition about another entity or situation.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.