Triple
T22553940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Douala |
E557628
|
entity |
| Predicate | portCodeUNLOCODE |
P1492
|
FINISHED |
| Object |
CMDLA
CMDLA is the UN/LOCODE identifier for the Port of Douala, Cameroon’s principal seaport and a major maritime gateway for Central Africa.
|
E1542631
|
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: CMDLA | Statement: [Port of Douala, portCodeUNLOCODE, CMDLA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CMDLA Context triple: [Port of Douala, portCodeUNLOCODE, CMDLA]
-
A.
DLA
DLA is a UK social security benefit that provides financial support to people with disabilities to help cover the extra costs of care and mobility.
-
B.
DLA
DLA is the standard abbreviation for a damped Lyman-alpha system, a type of quasar absorption feature indicating large reservoirs of neutral hydrogen gas in the universe.
-
C.
DLA
DLA is the commonly used abbreviation for the Delhi Legislative Assembly, the unicameral law-making body of the National Capital Territory of Delhi in India.
-
D.
DLA
DLA is the IATA airport code for Douala International Airport, the main air gateway to Douala, Cameroon.
-
E.
CMD
CMD is the three-letter station code used to identify Camden Town tube station on the London Underground network.
- 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: CMDLA Triple: [Port of Douala, portCodeUNLOCODE, CMDLA]
Generated description
CMDLA is the UN/LOCODE identifier for the Port of Douala, Cameroon’s principal seaport and a major maritime gateway for Central Africa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CMDLA Target entity description: CMDLA is the UN/LOCODE identifier for the Port of Douala, Cameroon’s principal seaport and a major maritime gateway for Central Africa.
-
A.
DLA
DLA is the standard abbreviation for a damped Lyman-alpha system, a type of quasar absorption feature indicating large reservoirs of neutral hydrogen gas in the universe.
-
B.
DLA
DLA is a UK social security benefit that provides financial support to people with disabilities to help cover the extra costs of care and mobility.
-
C.
DLA
DLA is the IATA airport code for Douala International Airport, the main air gateway to Douala, Cameroon.
-
D.
DLA
DLA is the commonly used abbreviation for the Delhi Legislative Assembly, the unicameral law-making body of the National Capital Territory of Delhi in India.
-
E.
CMD
CMD is the three-letter station code used to identify Camden Town tube station on the London Underground network.
- 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_69e11e59db848190b4272ecd2b690ffd |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f780fb88190836408c6de3d3966 |
completed | April 29, 2026, 1:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b2d6510648190aba36f0ad1bb4f81 |
completed | May 18, 2026, 3:16 p.m. |
| NEDg | Description generation | batch_6a0b364718308190937c3b7ae90ea9df |
completed | May 18, 2026, 3:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b37998f888190bb53c2429760321a |
completed | May 18, 2026, 4 p.m. |
Created at: April 16, 2026, 8:52 p.m.