Triple
T14324639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AFAS Circustheater |
E355183
|
entity |
| Predicate | hasBranding |
P11989
|
FINISHED |
| Object | AFAS |
E956319
|
NE FINISHED |
How this triple was built (2 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: AFAS | Statement: [AFAS Circustheater, hasBranding, AFAS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AFAS Context triple: [AFAS Circustheater, hasBranding, AFAS]
-
A.
AFAS
AFAS is a regional agreement among ASEAN member states aimed at progressively liberalizing trade in services to enhance economic integration and competitiveness in Southeast Asia.
-
B.
AFAS Live
AFAS Live is a major indoor music and events venue in Amsterdam, Netherlands, known for hosting concerts, shows, and large-scale entertainment performances.
-
C.
AFAS Software
chosen
AFAS Software is a Dutch company that develops business and accounting software solutions for organizations in various sectors.
-
D.
AFS
AFS is the National Rail station code for Ashford (Surrey) railway station in England.
-
E.
AFAC
AFAC is Mexico’s Federal Civil Aviation Agency responsible for regulating and overseeing civil aviation activities in the country.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de883e6a288190b6c22f630a1eef3c |
completed | April 14, 2026, 6:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd468e263c81909d7261bcfd949579 |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:13 a.m.