Triple
T8127399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OIII |
E189765
|
entity |
| Predicate | hasIcaoCode |
P419
|
FINISHED |
| Object | OIII |
E189765
|
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: OIII | Statement: [OIII, hasIcaoCode, OIII]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OIII Context triple: [OIII, hasIcaoCode, OIII]
-
A.
OIII
chosen
OIII is the ICAO airport code for Mehrabad International Airport in Tehran, Iran.
-
B.
OII
OII is the stock ticker symbol for Oceaneering International, an engineering and applied technology company specializing in subsea services and products for the offshore energy industry.
-
C.
OIIR
OIIR is the Office of International and Interagency Relations, a U.S. government office that coordinates collaboration and policy engagement between its parent agency and both foreign and domestic partner organizations.
-
D.
OIOI
OIOI is a Japanese department store and retail brand operated by the Marui Group, known for its fashion-focused shopping complexes in urban areas.
-
E.
O.
O. is the middle initial of Mark O. Hatfield, the long-serving U.S. Senator and former Governor of Oregon.
- 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_69ca82bb74848190afb1f18640632c10 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb438ff4e08190a9af0f3e6401c9b2 |
completed | March 31, 2026, 3:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbebd0d0481908eb6989d1822421a |
completed | April 1, 2026, 6:44 a.m. |
Created at: March 30, 2026, 5:34 p.m.