Triple
T17407614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geißenklösterle |
E423259
|
entity |
| Predicate | materialUsedForInstruments |
P127349
|
FINISHED |
| Object | bird bone |
—
|
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: bird bone | Statement: [Geißenklösterle, materialUsedForInstruments, bird bone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialUsedForInstruments Context triple: [Geißenklösterle, materialUsedForInstruments, bird bone]
-
A.
instruments
Indicates that an agent uses a tool, device, or means to carry out an action or achieve an effect.
-
B.
notableInstrument
Indicates that an entity is especially known for playing or being associated with a particular musical instrument.
-
C.
playedInstrument
Indicates that an entity performed or used a particular musical instrument.
-
D.
musicInstrumentation
Indicates the specific instruments or instrumental forces used to perform a piece of music.
-
E.
numberOfInstruments
Indicates the quantitative count of instruments associated with or involved in a given entity or event.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b08d5a881909e7a5b2ae2c60898 |
completed | April 19, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
| PDg | Predicate description generation | batch_69e3b2a33e8481908fa6ef45290d08aa |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:46 a.m.