Triple
T7808347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OAG DC |
E180612
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | OAG DC |
E180612
|
NE 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: OAG DC | Statement: [OAG DC, shortName, OAG DC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OAG DC Context triple: [OAG DC, shortName, OAG DC]
-
A.
OAG DC
chosen
OAG DC is the government agency that serves as the chief legal office for the District of Columbia, representing the city in legal matters and enforcing its laws.
-
B.
OAG
OAG is the independent office responsible for auditing and overseeing the financial operations and performance of Florida’s state agencies and related entities.
-
C.
AGS Airports
AGS Airports is a UK-based airport management company that owns and operates several regional airports in Scotland and England.
-
D.
Aeroport
Aeroport is a Moscow Metro station on the Zamoskvoretskaya Line, named after the nearby Khodynka Aerodrome area.
-
E.
Flughafen
Flughafen is the Nuremberg U-Bahn station that serves Nuremberg Airport, providing direct metro access between the airport and the city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca827f6f148190beca4e245b993506 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf63b3ebc819088dcf4c58b80b18a |
completed | March 30, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb145b93788190a89f26dacbd0b437 |
completed | March 31, 2026, 12:24 a.m. |
Created at: March 30, 2026, 4:36 p.m.