Triple
T20526392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tudeh Party of Iran |
E503946
|
entity |
| Predicate | hadPeakInfluenceIn |
P55472
|
FINISHED |
| Object | 1940s |
—
|
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: 1940s | Statement: [Tudeh Party of Iran, hadPeakInfluenceIn, 1940s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPeakInfluenceIn Context triple: [Tudeh Party of Iran, hadPeakInfluenceIn, 1940s]
-
A.
hadPeakInfluencePeriod
chosen
Indicates the time span during which an entity exerted its greatest or most significant influence.
-
B.
hasSignificantInfluenceIn
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
-
C.
hadInfluenceOn
Indicates that one entity affected, shaped, or contributed to the development, behavior, or characteristics of another entity.
-
D.
hasEnduringInfluence
Indicates that one entity continues to significantly affect, shape, or inform another entity or context over an extended period of time.
-
E.
hasEnduringInfluenceOn
Indicates that one entity exerts a lasting, long-term impact on another entity’s state, development, or behavior.
- 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a066402081909dd53830eb637ad0 |
completed | April 20, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:37 a.m.