Triple
T8159646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malard County |
E190542
|
entity |
| Predicate | hasMajorUrbanArea |
P11388
|
FINISHED |
| Object | Malard |
E715266
|
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: Malard | Statement: [Malard County, hasMajorUrbanArea, Malard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malard Context triple: [Malard County, hasMajorUrbanArea, Malard]
-
A.
Malard
chosen
Malard is a city in Tehran Province, Iran, known as an urban and administrative center within the Malard County region.
-
B.
Mauzy
Mauzy is the surname of American actress Mackenzie Mauzy, known for her roles in television and film.
-
C.
Marly
Marly is a French locality historically associated with royal architecture and landscape design, notably linked to the works of architect Jules Hardouin-Mansart.
-
D.
Rhyll
Rhyll is a small coastal village and fishing port on Phillip Island in Victoria, Australia, known for its tranquil bay views and access to local wildlife and marine activities.
-
E.
Mümling
The Mümling is a river in the Odenwald region of Germany that flows through Hesse and Bavaria before joining the Main.
- 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_69ca82bfeb6481909d07b91b5cf69f59 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb45537d248190a0e998b6d336e6e1 |
completed | March 31, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd3471def08190a221e92fc4a2e9d7 |
completed | April 1, 2026, 3:06 p.m. |
Created at: March 30, 2026, 5:38 p.m.