Triple
T15378054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B. Inspired |
E367720
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | OG |
unclear NED1
|
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: OG | Statement: [B. Inspired, hasTrack, OG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OG Context triple: [B. Inspired, hasTrack, OG]
-
A.
OG
OG is the vehicle registration code for the German district of Ortenaukreis in the state of Baden-Württemberg.
-
B.
OG
OG is the commonly used abbreviation for the Astronomical Observatory of the University of Warsaw, a major Polish center for astronomical research and education.
-
C.
GD
GD is the vehicle registration code used on license plates for cars registered in the city of Gdańsk, Poland.
-
D.
GD
GD is the vehicle registration code assigned to the town of Aalen in the German state of Baden-Württemberg.
-
E.
GD
GD is the abbreviation for Guangdong, a populous and economically significant coastal province in southern China.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e6044488190b0499db109f7f821 |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b56dd1c81909a3933330e85fe0e |
completed | May 9, 2026, 10:24 a.m. |
Created at: April 10, 2026, 3:18 a.m.