Triple
T1100569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ASEAN Secretariat |
E24369
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
ASEC
ASEC is the commonly used abbreviation for the ASEAN Secretariat, the administrative body that supports and coordinates the activities of the Association of Southeast Asian Nations.
|
E127084
|
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: ASEC | Statement: [ASEAN Secretariat, shortName, ASEC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ASEC Context triple: [ASEAN Secretariat, shortName, ASEC]
-
A.
ECASA
ECASA is a Cuban state-owned company responsible for managing and operating the country’s civil airports and air terminals.
-
B.
ECA
ECA is a regional United Nations commission focused on promoting economic and social development across the African continent.
-
C.
ECA
The Economic Cooperation Administration (ECA) was the U.S. government agency responsible for administering the Marshall Plan to aid European economic recovery after World War II.
-
D.
SCSE
SCSE is the ICAO airport code assigned to La Florida Airport in Chile.
-
E.
ASEA-UNINET
ASEA-UNINET is an international academic network that promotes cooperation in higher education and research between universities in Europe and Southeast Asia.
- 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: ASEC Triple: [ASEAN Secretariat, shortName, ASEC]
Generated description
ASEC is the commonly used abbreviation for the ASEAN Secretariat, the administrative body that supports and coordinates the activities of the Association of Southeast Asian Nations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ASEC Target entity description: ASEC is the commonly used abbreviation for the ASEAN Secretariat, the administrative body that supports and coordinates the activities of the Association of Southeast Asian Nations.
-
A.
ECASA
ECASA is a Cuban state-owned company responsible for managing and operating the country’s civil airports and air terminals.
-
B.
ECA
ECA is a regional United Nations commission focused on promoting economic and social development across the African continent.
-
C.
ECA
The Economic Cooperation Administration (ECA) was the U.S. government agency responsible for administering the Marshall Plan to aid European economic recovery after World War II.
-
D.
SCSE
SCSE is the ICAO airport code assigned to La Florida Airport in Chile.
-
E.
ASEA-UNINET
ASEA-UNINET is an international academic network that promotes cooperation in higher education and research between universities in Europe and Southeast Asia.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9c079f48190a0e0ddda182f7a01 |
completed | March 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4c47dbf88190a1898d7bda32ecb2 |
completed | March 7, 2026, 4:03 p.m. |
| NEDg | Description generation | batch_69ac4feb86c88190abaed60e0782fec6 |
completed | March 7, 2026, 4:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac509b6fe48190973bbfabdc976541 |
completed | March 7, 2026, 4:21 p.m. |
Created at: March 1, 2026, 7:43 p.m.