Triple
T1979314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ley |
E42987
|
entity |
| Predicate | hasNameFunction |
P33033
|
FINISHED |
| Object | first name |
—
|
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: first name | Statement: [Ley, hasNameFunction, first name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameFunction Context triple: [Ley, hasNameFunction, first name]
-
A.
hasProperName
Indicates that an entity is associated with a specific proper name used to uniquely identify it.
-
B.
hasComponentName
Indicates that an entity includes or is associated with a component identified by a specific name.
-
C.
hasTypeName
Indicates that an entity is associated with a specific type name used to classify or identify its kind.
-
D.
hasGenericName
Indicates that an entity is associated with a non-brand, generic name that designates its general type or class.
-
E.
hasCodeName
Indicates that an entity is known or referred to by a particular alternative name or alias, often used for secrecy or distinction.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb43011188190b6a41c004e9e4802 |
completed | March 7, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_69abaff9a09c8190a81fa13f4b85bc79 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb09b27e88190bff164040fef6d7e |
completed | March 7, 2026, 4:59 a.m. |
Created at: March 4, 2026, 7:36 p.m.