Triple
T14452030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kangra Airport |
E358360
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
DHM
DHM is the IATA airport code for Kangra Airport, a regional airport serving Dharamshala and the surrounding Kangra Valley in Himachal Pradesh, India.
|
E1098907
|
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: DHM | Statement: [Kangra Airport, IATAcode, DHM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DHM Context triple: [Kangra Airport, IATAcode, DHM]
-
A.
DHM
DHM is the National Rail station code for Durham railway station in County Durham, England.
-
B.
DHM
DHM is the commonly used abbreviation for the German Historical Museum in Berlin, a major institution dedicated to documenting and presenting German history.
-
C.
DHMİ
DHMİ is Turkey’s state-owned General Directorate of State Airports Authority, responsible for operating and managing the country’s major airports and air navigation services.
-
D.
DMH
DMH is the Massachusetts state agency responsible for overseeing and providing public mental health services and supports.
-
E.
HdM
HdM is the commonly used abbreviation for Stuttgart Media University, a German university specializing in media, information, and communication studies.
- 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: DHM Triple: [Kangra Airport, IATAcode, DHM]
Generated description
DHM is the IATA airport code for Kangra Airport, a regional airport serving Dharamshala and the surrounding Kangra Valley in Himachal Pradesh, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DHM Target entity description: DHM is the IATA airport code for Kangra Airport, a regional airport serving Dharamshala and the surrounding Kangra Valley in Himachal Pradesh, India.
-
A.
DHM
DHM is the commonly used abbreviation for the German Historical Museum in Berlin, a major institution dedicated to documenting and presenting German history.
-
B.
DHM
DHM is the National Rail station code for Durham railway station in County Durham, England.
-
C.
DHMİ
DHMİ is Turkey’s state-owned General Directorate of State Airports Authority, responsible for operating and managing the country’s major airports and air navigation services.
-
D.
DMH
DMH is the Massachusetts state agency responsible for overseeing and providing public mental health services and supports.
-
E.
HdM
HdM is the commonly used abbreviation for Stuttgart Media University, a German university specializing in media, information, and communication studies.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de916244948190bb09d1bfc485ba50 |
completed | April 14, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5be12da481909b11290965ec48da |
completed | May 8, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69fd5de2ebac81908042f6696400a74d |
completed | May 8, 2026, 3:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd5e6927c88190add8d31989bec043 |
completed | May 8, 2026, 3:54 a.m. |
Created at: April 10, 2026, 1:19 a.m.