Triple
T9006751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ostallgäu |
E215162
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
OAL
OAL is the vehicle registration code used on license plates for the Ostallgäu district in Bavaria, Germany.
|
E770756
|
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: OAL | Statement: [Ostallgäu, vehicleRegistrationCode, OAL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OAL Context triple: [Ostallgäu, vehicleRegistrationCode, OAL]
-
A.
OAL
OAL is the abbreviation for the Ordre des Arts et des Lettres, a French order of merit that honors significant contributions to the arts and literature.
-
B.
OAL
OAL is the California Office of Administrative Law, the state agency responsible for reviewing and approving regulations proposed by California’s executive branch agencies.
-
C.
AUL
AUL is the ICAO airline designator assigned to the Russian carrier Smartavia.
-
D.
AUL
AUL is an abbreviation used in Massachusetts environmental regulation to denote an Activity and Use Limitation, a legal restriction placed on how a contaminated property may be used.
-
E.
OLA
OLA is the commonly used acronym for the United Nations Office of Legal Affairs, which provides legal advice and support to UN organs and specialized agencies.
- 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: OAL Triple: [Ostallgäu, vehicleRegistrationCode, OAL]
Generated description
OAL is the vehicle registration code used on license plates for the Ostallgäu district in Bavaria, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: OAL Target entity description: OAL is the vehicle registration code used on license plates for the Ostallgäu district in Bavaria, Germany.
-
A.
OAL
OAL is the abbreviation for the Ordre des Arts et des Lettres, a French order of merit that honors significant contributions to the arts and literature.
-
B.
OAL
OAL is the California Office of Administrative Law, the state agency responsible for reviewing and approving regulations proposed by California’s executive branch agencies.
-
C.
AUL
AUL is the ICAO airline designator assigned to the Russian carrier Smartavia.
-
D.
AUL
AUL is an abbreviation used in Massachusetts environmental regulation to denote an Activity and Use Limitation, a legal restriction placed on how a contaminated property may be used.
-
E.
OLA
OLA is the commonly used acronym for the United Nations Office of Legal Affairs, which provides legal advice and support to UN organs and specialized agencies.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69bc6e208190b0c01e3761c04799 |
completed | April 1, 2026, 12:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0e7f090819093c7af51c3979978 |
completed | April 3, 2026, 2:38 p.m. |
| NEDg | Description generation | batch_69cfd17e5850819087fbb60fdc612fd9 |
completed | April 3, 2026, 2:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfd215204c8190886cc071f100aab6 |
completed | April 3, 2026, 2:43 p.m. |
Created at: March 30, 2026, 7:05 p.m.