Triple
T1509983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dibrugarh Airport |
E33991
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
VEMN
VEMN is the ICAO airport code assigned to Dibrugarh Airport in Assam, India.
|
E173225
|
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: VEMN | Statement: [Dibrugarh Airport, ICAOcode, VEMN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VEMN Context triple: [Dibrugarh Airport, ICAOcode, VEMN]
-
A.
VU
VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
-
B.
VEN
VEN is the three-letter ISO 3166-1 alpha-3 country code assigned to Venezuela for international identification and data standards.
-
C.
VMI
VMI is a public military college in Lexington, Virginia, known for its rigorous academic and military training programs.
-
D.
VNM
VNM is the three-letter ISO 3166-1 alpha-3 country code assigned to Vietnam.
-
E.
VE
VE is the two-letter ISO 3166-1 alpha-2 country code assigned to Venezuela for international standardization and identification purposes.
- 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: VEMN Triple: [Dibrugarh Airport, ICAOcode, VEMN]
Generated description
VEMN is the ICAO airport code assigned to Dibrugarh Airport in Assam, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: VEMN Target entity description: VEMN is the ICAO airport code assigned to Dibrugarh Airport in Assam, India.
-
A.
VU
VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
-
B.
VEN
VEN is the three-letter ISO 3166-1 alpha-3 country code assigned to Venezuela for international identification and data standards.
-
C.
VMI
VMI is a public military college in Lexington, Virginia, known for its rigorous academic and military training programs.
-
D.
VNM
VNM is the three-letter ISO 3166-1 alpha-3 country code assigned to Vietnam.
-
E.
VE
VE is the two-letter ISO 3166-1 alpha-2 country code assigned to Venezuela for international standardization and identification purposes.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a8891e9da881909d0b12f1bc05863f |
completed | March 4, 2026, 7:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad233c254c8190b52b34526c9cb3cb |
completed | March 8, 2026, 7:20 a.m. |
| NEDg | Description generation | batch_69ad242d20448190a27ff7414d9cff21 |
completed | March 8, 2026, 7:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad24e6e9688190a20c67c181936e98 |
completed | March 8, 2026, 7:27 a.m. |
Created at: March 4, 2026, 7:24 p.m.