Triple
T7437768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amapá |
E171661
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | AP |
E102106
|
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: AP | Statement: [Amapá, vehicleRegistrationCode, AP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AP Context triple: [Amapá, vehicleRegistrationCode, AP]
-
A.
AP
AP is the standard abbreviation for the Pacific Alliance, a Latin American trade bloc focused on economic integration and free movement of goods, services, capital, and people among its member countries.
-
B.
AP
AP is a U.S.-based college-level program and exam system for high school students that can earn them advanced placement or credit at many universities.
-
C.
AP
AP is the vehicle registration code used on license plates for vehicles registered in the Argolis regional unit of Greece.
-
D.
AP
chosen
AP is the official vehicle registration code for the Indian state of Andhra Pradesh.
-
E.
AAP
AAP is the commonly used abbreviation for Cornell University's College of Architecture, Art, and Planning, which focuses on design, visual arts, and urban and regional planning education.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34aa3388190ac300cf934042d78 |
completed | March 27, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8278cd9cc8190b88767c1432b3007 |
completed | March 28, 2026, 7:10 p.m. |
Created at: March 27, 2026, 3:13 p.m.