Triple
T27801017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jackson Town Square |
E702239
|
entity |
| Predicate | antlersSourcedFrom |
P131523
|
FINISHED |
| Object | National Elk Refuge |
—
|
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: National Elk Refuge | Statement: [Jackson Town Square, antlersSourcedFrom, National Elk Refuge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antlersSourcedFrom Context triple: [Jackson Town Square, antlersSourcedFrom, National Elk Refuge]
-
A.
antlerType
Indicates the specific kind or classification of antlers that an entity possesses or is associated with.
-
B.
antlersPresentIn
Indicates that antlers are physically present within or on the specified location or entity.
-
C.
antlerLength
Indicates the measured length of an entity’s antlers in some specified unit.
-
D.
antlerTinesTypicalCount
Indicates the usual or characteristic number of tines (points) present on an individual's antlers.
-
E.
sourceAnimal
chosen
Indicates that one entity is the animal from which another entity (such as a product, material, or sample) is derived or obtained.
- 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_69ef8408e0588190977cffa32dc33a29 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6383625cc8190aa223d8ef655743c |
completed | May 2, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69f6318ae6f08190b3f85f9201046a15 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 5:34 p.m.