Triple
T17496288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muslim Mosque, Inc. |
E426069
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | MMI |
—
|
NE NERFINISHED |
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: MMI | Statement: [Muslim Mosque, Inc., abbreviation, MMI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MMI Context triple: [Muslim Mosque, Inc., abbreviation, MMI]
-
A.
MMI
chosen
MMI is an abbreviation for Muslim Mosque, Inc., a religious organization associated with the Muslim community.
-
B.
MMTU
MMTU is the ICAO airport code for Tulum International Airport in Tulum, Quintana Roo, Mexico.
-
C.
OMM
OMM is the post-nominal letters used to denote membership in the Canadian Order of Military Merit, an honor recognizing exceptional service and devotion by members of the Canadian Armed Forces.
-
D.
HMI
HMI is a key instrument on NASA’s Solar Dynamics Observatory that measures the Sun’s magnetic field and surface oscillations to study solar activity and interior structure.
-
E.
HMI
HMI is a renowned Indian mountaineering institute in Darjeeling that trains climbers and promotes Himalayan exploration and adventure sports.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4520e9c8c8190aa955766bc915d26 |
completed | April 19, 2026, 3:54 a.m. |
Created at: April 10, 2026, 5:48 a.m.