Triple
T19318677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Angeles municipal elections |
E483162
|
entity |
| Predicate | termLengthForMayor |
P540
|
FINISHED |
| Object | 4 years |
—
|
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 years | Statement: [Los Angeles municipal elections, termLengthForMayor, 4 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termLengthForMayor Context triple: [Los Angeles municipal elections, termLengthForMayor, 4 years]
-
A.
hasMayorTerm
Indicates that a specified individual holds or has held the office of mayor for a particular jurisdiction during a defined term.
-
B.
termLength
chosen
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
-
C.
numberOfTermsAsMayor
Indicates the number of distinct terms an individual has served in the role of mayor.
-
D.
termLengthNumber
Indicates the numerical value representing the duration or length of a specified term.
-
E.
electsTermLength
Indicates the length of time for which an entity is elected to hold a particular position or office.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e60d868dd48190b1439a5f4ff58c48 |
completed | April 20, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0ef66881909d489d634eee817a |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:32 p.m.