Triple
T2354434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trigger (guitar) |
E47521
|
entity |
| Predicate | stringType |
P28296
|
FINISHED |
| Object | nylon |
—
|
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: nylon | Statement: [Trigger (guitar), stringType, nylon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stringType Context triple: [Trigger (guitar), stringType, nylon]
-
A.
hasStringType
chosen
Indicates that an entity is associated with, defined by, or constrained to a specific string data type.
-
B.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
-
C.
nameType
Indicates the specific category or type of a name associated with an entity (e.g., legal name, nickname, alias, or preferred name).
-
D.
symbolType
Indicates the classification or category of a symbol based on its role, form, or function within a given system.
-
E.
linguisticType
Indicates the type or category of language or linguistic system associated with an entity (e.g., spoken, signed, written, or other linguistic modality).
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abcb802da08190980100444010f91e |
completed | March 7, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69abc5981ce48190a3f7852d28276e11 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:54 p.m.