Triple
T36658880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Accipiter cooperii |
E905065
|
entity |
| Predicate | similarCommonName |
P106359
|
FINISHED |
| Object | sharp-shinned hawk |
—
|
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: sharp-shinned hawk | Statement: [Accipiter cooperii, similarCommonName, sharp-shinned hawk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: similarCommonName Context triple: [Accipiter cooperii, similarCommonName, sharp-shinned hawk]
-
A.
namedForSimilarityTo
chosen
Indicates that one entity is given its name because of a perceived resemblance or likeness to another entity.
-
B.
otherCommonName
Indicates that an entity is known by an additional, alternative common name besides its primary one.
-
C.
moreCommonPublicName
Indicates that one name is used more frequently or popularly in public contexts than another alternative name for the same entity.
-
D.
sharesGivenNameWith
Indicates that two entities have the same given (first) name.
-
E.
similarCredentialAs
Indicates that one credential is considered equivalent or closely matching another in terms of content, level, or recognition.
- 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_69f76e6e3b908190970251b30f76ad71 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c77a12fc8190b309606d38a8e145 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.