Triple
T22273768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur |
E550547
|
entity |
| Predicate | hasGNBCCode |
P147658
|
FINISHED |
| Object | FANVX |
—
|
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: FANVX | Statement: [Arthur, hasGNBCCode, FANVX]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGNBCCode Context triple: [Arthur, hasGNBCCode, FANVX]
-
A.
hasGssCode
Indicates that an entity is associated with a specific GSS (Government Statistical Service) code used for official geographic or statistical identification.
-
B.
hasICBCode
Indicates that an entity is associated with a specific ICB (Industry Classification Benchmark) code that classifies its industry or sector.
-
C.
hasONSCode
Indicates that an entity is associated with a specific code assigned by the Office for National Statistics (ONS) for identification or classification purposes.
-
D.
hasGardinerCode
Indicates that an entity (typically an Egyptian hieroglyph) is associated with a specific Gardiner sign list code used for its classification.
-
E.
hasNOCCode
Indicates that an entity is associated with a specific National Occupational Classification (NOC) code that categorizes its occupation or job type.
- 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_69e11e43d8208190aff4f9cf7f2c2a8a |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f14ea547e4819098baf88f3c605242 |
completed | April 29, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e72ff0363081909f794d19c8a64837 |
completed | April 21, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e7342ce08c8190bc0a7085f4a952e7 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 8:40 p.m.