Triple
T9286759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pecora |
E223412
|
entity |
| Predicate | hasCircaFirstAppearance |
P4114
|
FINISHED |
| Object | Oligocene |
—
|
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: Oligocene | Statement: [Pecora, hasCircaFirstAppearance, Oligocene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCircaFirstAppearance Context triple: [Pecora, hasCircaFirstAppearance, Oligocene]
-
A.
settingOfFirstAppearance
Indicates the location or context in which an entity is first introduced or appears.
-
B.
firstAppearanceFor
Indicates that an entity marks the initial occurrence or debut of another entity within a given context or medium.
-
C.
firstPublicationYearOfAppearance
Indicates the year in which an entity (such as a work or character) first appeared in a published form.
-
D.
firstAppeared
chosen
Indicates the earliest known time or context in which an entity was introduced, observed, or came into existence.
-
E.
firstPopularAppearance
Indicates the earliest notable or widely recognized appearance of an entity in a public or popular context.
- 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_69ca8422ddf881908a3f8f876c9f53aa |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0821b1108190b16e9570b09a14de |
completed | April 1, 2026, 11:57 a.m. |
| PD | Predicate disambiguation | batch_69cc7a576ec88190bbb787eb82e2e539 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:35 p.m.