Triple
T593674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SUE the T. rex |
E17330
|
entity |
| Predicate | hasReplicaDisplays |
P16046
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [SUE the T. rex, hasReplicaDisplays, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReplicaDisplays Context triple: [SUE the T. rex, hasReplicaDisplays, yes]
-
A.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
-
B.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
-
C.
hasDisplayType
Indicates the type or category of display associated with an entity, such as the format, mode, or presentation style used to show its content.
-
D.
hasRetiredNumbersDisplay
Indicates that an entity features a display or presentation of numbers that have been officially retired (such as jersey numbers).
-
E.
supportsMultipleDataAndDisplayProtocols
Indicates that an entity is capable of handling more than one type of data protocol and more than one type of display protocol.
- F. None of above. chosen
Provenance (4 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bd15c5881909b59ed4c88687e7b |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cd7d3c8190af008acf34a2293b |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985ada988190aaea628a9b55bca4 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:33 p.m.