Triple
T31051366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Puerto Rican Pepperpot |
E791274
|
entity |
| Predicate | hasRealPerson |
P102195
|
FINISHED |
| Object | Olga San Juan |
—
|
NE NERFINISHED |
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: Olga San Juan | Statement: [The Puerto Rican Pepperpot, hasRealPerson, Olga San Juan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRealPerson Context triple: [The Puerto Rican Pepperpot, hasRealPerson, Olga San Juan]
-
A.
basedOnRealPersonFor
Indicates that one entity is created, modeled, or inspired using a specific real person as its basis.
-
B.
realPerson
chosen
Indicates that the referenced entity corresponds to an actual human individual, as opposed to a fictional, anonymous, or non-human entity.
-
C.
hasPersona
Indicates that an entity possesses or is associated with a particular persona, role, or character profile.
-
D.
hasFrontPerson
Indicates that an entity is represented, led, or fronted publicly by a specific person.
-
E.
isFullyHuman
Indicates that an entity possesses all defining characteristics of a human being, without any non-human or partial-human aspects.
- 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_69f224cb08908190ba71ad9aa87518ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00cbae75988190974f5b45a2e62326 |
completed | May 10, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_6a00cabe4c5881909cca5efbe494e0d1 |
completed | May 10, 2026, 6:13 p.m. |
Created at: April 29, 2026, 9 p.m.