Triple
T36826000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N-1 |
E910011
|
entity |
| Predicate | registrationCode |
P41462
|
FINISHED |
| Object | N-1 |
—
|
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: N-1 | Statement: [N-1, registrationCode, N-1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: registrationCode Context triple: [N-1, registrationCode, N-1]
-
A.
registrationOrCode
Indicates that there exists either a formal registration or an associated code linking the related entities in an equivalent identifying or authorizing role.
-
B.
licenceCode
Indicates that one entity is associated with a specific license identifier or code that governs its permitted use or distribution.
-
C.
boardCode
Indicates the specific code assigned to a board that identifies or distinguishes it from other boards.
-
D.
registrationNumber
chosen
Indicates the unique identifier assigned to an entity as part of an official or formal registration process.
-
E.
registrationCodeForDistrictSeat
Indicates that a specific registration code is assigned to a particular district seat.
- 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_69f76e7dd13c81908c60b05adb49eeb5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.