Triple
T8929973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MAN Truck & Bus |
E212627
|
entity |
| Predicate | formerParentOrganization |
P5106
|
FINISHED |
| Object | MAN SE |
E37749
|
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: MAN SE | Statement: [MAN Truck & Bus, formerParentOrganization, MAN SE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MAN SE Context triple: [MAN Truck & Bus, formerParentOrganization, MAN SE]
-
A.
MAN
MAN is the three-letter IATA airport code for Manchester Airport, a major international airport serving the Greater Manchester area in England.
-
B.
MAN
chosen
MAN is a German commercial vehicle and engineering company best known for manufacturing trucks, buses, and diesel engines.
-
C.
MANN
MANN is a major Italian archaeological museum in Naples renowned for its extensive collections of Greek, Roman, and particularly Pompeian antiquities.
-
D.
Manf
Manf is the Arabic name for the ancient Egyptian city of Memphis, a historically significant capital near modern-day Cairo.
-
E.
Mene
Mene is an epithet of the Greek moon goddess Selene, emphasizing her aspect as the personification of the lunar month and its cyclical phases.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6676d5d881908ce78cbb5561a68b |
completed | April 1, 2026, 12:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba63544081909394500f28b34ccb |
completed | April 3, 2026, 1:02 p.m. |
Created at: March 30, 2026, 6:57 p.m.