Triple
T32025320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anand Variation |
E817801
|
entity |
| Predicate | hasECOCode |
P174436
|
FINISHED |
| Object | D43 |
—
|
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: D43 | Statement: [Anand Variation, hasECOCode, D43]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasECOCode Context triple: [Anand Variation, hasECOCode, D43]
-
A.
hasIneCode
Indicates that an entity is associated with a specific INE (national statistics or education) code that identifies it in an official registry.
-
B.
hasFeatureCode
Indicates that an entity is associated with a specific feature identifier or code that characterizes one of its properties or attributes.
-
C.
hasICBCode
Indicates that an entity is associated with a specific ICB (Industry Classification Benchmark) code that classifies its industry or sector.
-
D.
hasINSEECODE
Indicates that an entity is associated with a specific INSEE code, identifying it within the French national statistical and administrative system.
-
E.
hasESODesignation
Indicates that an entity is assigned a specific designation or identifier by the European Southern Observatory (ESO).
- 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_69f348fb04e4819081f4eab040ed7959 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c2451e108190a73ccfdc99203d55 |
completed | May 3, 2026, 3:34 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
| PDg | Predicate description generation | batch_69f6c1b666188190ac43c3011a7df048 |
completed | May 3, 2026, 3:32 a.m. |
Created at: May 1, 2026, 12:17 a.m.