Triple
T11422968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dimapur |
E270671
|
entity |
| Predicate | airportICAOcode |
P419
|
FINISHED |
| Object |
VEMR
VEMR is the ICAO airport code for Dimapur Airport, a domestic airport serving the city of Dimapur in Nagaland, India.
|
E924615
|
NE FINISHED |
How this triple was built (4 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: VEMR | Statement: [Dimapur, airportICAOcode, VEMR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VEMR Context triple: [Dimapur, airportICAOcode, VEMR]
-
A.
VEMN
VEMN is the ICAO airport code assigned to Dibrugarh Airport in Assam, India.
-
B.
VEIM
VEIM is the ICAO airport code for Imphal International Airport, the main air gateway to the Indian state of Manipur.
-
C.
VOMM
VOMM is the ICAO airport code for Chennai International Airport, a major aviation hub in southern India.
-
D.
VES
VES is an abbreviation for the Virtual Execution System, a runtime environment designed to execute managed code in a platform-independent manner.
-
E.
VMC
VMC is the Venus Monitoring Camera, a wide-angle imaging instrument on the European Space Agency’s Venus Express spacecraft used to study Venus’s atmosphere and cloud dynamics.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: VEMR Triple: [Dimapur, airportICAOcode, VEMR]
Generated description
VEMR is the ICAO airport code for Dimapur Airport, a domestic airport serving the city of Dimapur in Nagaland, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: VEMR Target entity description: VEMR is the ICAO airport code for Dimapur Airport, a domestic airport serving the city of Dimapur in Nagaland, India.
-
A.
VEMN
VEMN is the ICAO airport code assigned to Dibrugarh Airport in Assam, India.
-
B.
VEIM
VEIM is the ICAO airport code for Imphal International Airport, the main air gateway to the Indian state of Manipur.
-
C.
VOMM
VOMM is the ICAO airport code for Chennai International Airport, a major aviation hub in southern India.
-
D.
VES
VES is an abbreviation for the Virtual Execution System, a runtime environment designed to execute managed code in a platform-independent manner.
-
E.
VMC
VMC is the Venus Monitoring Camera, a wide-angle imaging instrument on the European Space Agency’s Venus Express spacecraft used to study Venus’s atmosphere and cloud dynamics.
- F. None of above. chosen
Provenance (5 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d801b357e88190ace56d36a945688f |
completed | April 9, 2026, 7:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5b8a1e88c8190994bea88a0490e60 |
completed | April 20, 2026, 5:24 a.m. |
| NEDg | Description generation | batch_69e5c28e2dd481909b45a43b5825f393 |
completed | April 20, 2026, 6:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5c4722c348190a4c49edb1f6df240 |
completed | April 20, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:34 p.m.