Triple
T13160863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Djibouti–Ambouli International Airport |
E312721
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
HDAM
HDAM is the ICAO airport code for Djibouti–Ambouli International Airport, the main international airport serving Djibouti.
|
E1024447
|
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: HDAM | Statement: [Djibouti–Ambouli International Airport, ICAOcode, HDAM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HDAM Context triple: [Djibouti–Ambouli International Airport, ICAOcode, HDAM]
-
A.
HDA
HDA is the ICAO airline designator assigned to Cathay Dragon, the former Hong Kong-based regional carrier of the Cathay Pacific Group.
-
B.
HdM
HdM is the commonly used abbreviation for Stuttgart Media University, a German university specializing in media, information, and communication studies.
-
C.
HDX
HDX is an open humanitarian data platform that enables organizations to share, find, and use data for crisis preparedness and response.
-
D.
HDM
HDM is the National Rail station code for Haddenham and Thame Parkway railway station in Buckinghamshire, England.
-
E.
HDS
HDS is a high-dispersion spectrograph used on the Subaru Telescope for detailed spectroscopic studies of astronomical objects.
- 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: HDAM Triple: [Djibouti–Ambouli International Airport, ICAOcode, HDAM]
Generated description
HDAM is the ICAO airport code for Djibouti–Ambouli International Airport, the main international airport serving Djibouti.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HDAM Target entity description: HDAM is the ICAO airport code for Djibouti–Ambouli International Airport, the main international airport serving Djibouti.
-
A.
HDA
HDA is the ICAO airline designator assigned to Cathay Dragon, the former Hong Kong-based regional carrier of the Cathay Pacific Group.
-
B.
HdM
HdM is the commonly used abbreviation for Stuttgart Media University, a German university specializing in media, information, and communication studies.
-
C.
HDX
HDX is an open humanitarian data platform that enables organizations to share, find, and use data for crisis preparedness and response.
-
D.
HDM
HDM is the National Rail station code for Haddenham and Thame Parkway railway station in Buckinghamshire, England.
-
E.
HDS
HDS is a high-dispersion spectrograph used on the Subaru Telescope for detailed spectroscopic studies of astronomical objects.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c0971008190869e9de710f4c579 |
completed | April 10, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eaf2ae688190b3484989791977ce |
completed | May 3, 2026, 6:28 a.m. |
| NEDg | Description generation | batch_69f6ebec15188190a8a07af6eb447edf |
completed | May 3, 2026, 6:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ec7fe56481909e1ed69df593fa34 |
completed | May 3, 2026, 6:34 a.m. |
Created at: April 9, 2026, 9:12 p.m.