Triple
T10412090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HAECO |
E245415
|
entity |
| Predicate | industry |
P71
|
FINISHED |
| Object | MRO |
E633257
|
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: MRO | Statement: [HAECO, industry, MRO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MRO Context triple: [HAECO, industry, MRO]
-
A.
MRO
MRO is a NASA spacecraft orbiting Mars that conducts high-resolution imaging and scientific observations of the planet’s surface, atmosphere, and subsurface.
-
B.
MRO Division
chosen
MRO Division is a specialized unit of Hindustan Aeronautics Limited responsible for maintenance, repair, and overhaul services for aircraft and aerospace systems.
-
C.
9M-MRO
9M-MRO was the Boeing 777-200ER airliner operated by Malaysia Airlines that disappeared in 2014 while flying as Flight MH370.
-
D.
EMRO
EMRO is the World Health Organization’s regional office responsible for public health coordination and support across the Eastern Mediterranean region.
-
E.
M&R
M&R is the commonly used abbreviation for Murray & Roberts, a South African engineering and construction services company.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea0e17f081908fb16425f65e5808 |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fbfae96c8190ac496e9a1158afe4 |
completed | April 9, 2026, 7:20 p.m. |
Created at: April 6, 2026, 12:10 p.m.