Triple
T3733752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Congress of Veracruz |
E79128
|
entity |
| Predicate | hasLegislativePeriodLength |
P39902
|
FINISHED |
| Object | 3 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: 3 years | Statement: [Congress of Veracruz, hasLegislativePeriodLength, 3 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegislativePeriodLength Context triple: [Congress of Veracruz, hasLegislativePeriodLength, 3 years]
-
A.
legislativePeriod
Indicates the specific legislative term or session during which an action, event, or status is valid or took place.
-
B.
legislativePeriodicity
Indicates how frequently a legislative body or process recurs or is scheduled to occur over time.
-
C.
termLength
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
-
D.
electsTermLength
chosen
Indicates the length of time for which an entity is elected to hold a particular position or office.
-
E.
hasLegislativeSessionCount
Indicates the number of legislative sessions associated with a given legislative body, term, or jurisdiction.
- 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_69ad8b0e4650819090ad7cef094285e8 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb2457f08190a6b94e9895fced2c |
completed | March 8, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69adc04746588190b0dc535638f23546 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.