Triple
T1778546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aquila adalberti |
E39235
|
entity |
| Predicate | distinctiveMarking |
P32310
|
FINISHED |
| Object | pale shoulder patches |
—
|
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: pale shoulder patches | Statement: [Aquila adalberti, distinctiveMarking, pale shoulder patches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distinctiveMarking Context triple: [Aquila adalberti, distinctiveMarking, pale shoulder patches]
-
A.
mayHaveMarkings
Indicates that an entity is permitted or able to possess certain markings or distinguishing signs.
-
B.
markType
Indicates the specific category or kind of mark associated with or applied to an entity.
-
C.
aircraftMarking
Indicates a relationship where a marking, symbol, or identifier is applied to or displayed on an aircraft.
-
D.
hasCaseMarking
Indicates that a linguistic element (such as a noun or pronoun) bears a specific grammatical case marking that signals its syntactic or semantic role in a clause.
-
E.
distinguishingNotation
Indicates that one entity uses a specific notation or symbol to distinguish or differentiate another entity from similar ones.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab74dc9d1481908084ef07872a71f8 |
completed | March 7, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69aa61cf3ca881908641fd73ce2f7c9d |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab74db3dbc8190ab256a4e158062b8 |
completed | March 7, 2026, 12:44 a.m. |
Created at: March 4, 2026, 7:31 p.m.