Triple
T18110810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Investec Oaks |
E433467
|
entity |
| Predicate | hasTypicalField |
P2532
|
FINISHED |
| Object | three-year-old Thoroughbred fillies |
—
|
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: three-year-old Thoroughbred fillies | Statement: [Investec Oaks, hasTypicalField, three-year-old Thoroughbred fillies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalField Context triple: [Investec Oaks, hasTypicalField, three-year-old Thoroughbred fillies]
-
A.
typicalFields
chosen
Indicates the standard or commonly occurring attributes or data fields that are usually associated with an entity or record.
-
B.
hasBaseField
Indicates that one entity serves as the foundational or underlying field structure upon which another entity is defined or constructed.
-
C.
hasNumberOfFields
Indicates the specific count of fields or distinct data elements that an entity possesses.
-
D.
hasTypicalCharacterType
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
-
E.
hasMajorField
Indicates that an entity (such as a person or student) has a primary area of academic or professional specialization.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd2038081909515fb6d17495cbf |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:28 a.m.