Triple
T28182774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Nava-Grimón |
E716079
|
entity |
| Predicate | hasInfluenceSince |
P55472
|
FINISHED |
| Object | 16th–17th centuries |
—
|
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: 16th–17th centuries | Statement: [House of Nava-Grimón, hasInfluenceSince, 16th–17th centuries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInfluenceSince Context triple: [House of Nava-Grimón, hasInfluenceSince, 16th–17th centuries]
-
A.
hadPeakInfluencePeriod
chosen
Indicates the time span during which an entity exerted its greatest or most significant influence.
-
B.
hasHistoricalInfluenceFrom
Indicates that one entity’s characteristics, development, or significance have been shaped or affected by the past actions, ideas, or legacy of another entity.
-
C.
influencedIn
Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
-
D.
hadInfluenceOn
Indicates that one entity affected, shaped, or contributed to the development, behavior, or characteristics of another entity.
-
E.
hasInfluenceScope
Indicates the range or extent within which an entity’s influence, impact, or authority is effective or applicable.
- 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_69efd6b4fc5c81909dd88f01a8c2b35d |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69fd76d1e5208190a6f26651492d1e3c |
completed | May 8, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69fd702a226c81908edfda00f4be4130 |
completed | May 8, 2026, 5:10 a.m. |
Created at: April 27, 2026, 10:20 p.m.