Triple
T19822009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | COP25 |
E476216
|
entity |
| Predicate | CMANumber |
P137458
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [COP25, CMANumber, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CMANumber Context triple: [COP25, CMANumber, 2]
-
A.
MMSINumber
Indicates a relationship where a mobile subscriber is associated with a specific Mobile Station International ISDN Number (MSISDN) used to identify their phone line in a mobile network.
-
B.
codenameNumber
Indicates that an entity is assigned or associated with a specific codename identifier represented as a number.
-
C.
imoNumber
Indicates that an entity is associated with a specific International Maritime Organization (IMO) identification number used to uniquely identify ships and certain maritime structures.
-
D.
LAHCMNumber
Indicates that an entity has a specific LAHCM (likely a local or organizational) identification number assigned to it.
-
E.
BDNumber
Indicates that an entity is associated with a specific BD (Business Development or similar domain-specific) identification number used to uniquely reference it.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654ffb37c8190be540a793befe16c |
completed | April 20, 2026, 4:31 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bcf41c8190b685b5adf46a60fc |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:50 p.m.