Triple
T8837290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drensteinfurt |
E210296
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | WAF |
E601000
|
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: WAF | Statement: [Drensteinfurt, vehicleRegistrationCode, WAF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WAF Context triple: [Drensteinfurt, vehicleRegistrationCode, WAF]
-
A.
WAF
chosen
WAF is the vehicle registration code used on license plates for vehicles registered in the district of Warendorf in North Rhine-Westphalia, Germany.
-
B.
AWS WAF
AWS WAF is a cloud-based web application firewall service that helps protect web applications and APIs from common web exploits and bots.
-
C.
AIOWF
AIOWF is the collective body representing the international federations that govern sports featured in the Olympic Winter Games.
-
D.
WAFU
WAFU is the West African Football Union, a regional governing body for football in West Africa under the Confederation of African Football.
-
E.
WAS
WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
- 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc606adde08190825dbdabd199c025 |
completed | April 1, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf898a478c81908f138a78f331b87d |
completed | April 3, 2026, 9:34 a.m. |
Created at: March 30, 2026, 6:48 p.m.