Triple
T9800977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A4 |
E237835
|
entity |
| Predicate | passesNearCity |
P3945
|
FINISHED |
| Object | Metz |
E90772
|
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: Metz | Statement: [A4, passesNearCity, Metz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Metz Context triple: [A4, passesNearCity, Metz]
-
A.
Metz
chosen
Metz is a historic city in northeastern France known for its Gothic Saint-Stephen Cathedral, Roman and medieval heritage, and role as the capital of the Moselle department in the Grand Est region.
-
B.
Metz
Metz is a small rural village located in Vernon County in western Missouri, United States.
-
C.
Metz Métropole
Metz Métropole is an intercommunal metropolitan authority in northeastern France that coordinates urban planning, economic development, and public services for Metz and its surrounding municipalities.
-
D.
Maubeuge
Maubeuge is a fortified industrial town in northern France near the Belgian border, historically significant for its strategic military position.
-
E.
Bois-le-Duc
Bois-le-Duc is the French name for ’s-Hertogenbosch, a historic Dutch city known for its medieval architecture and cultural heritage in the southern Netherlands.
- 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_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda62a11a88190880e0cce24923b14 |
completed | April 1, 2026, 11:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d299b0ed588190ae5fe6e87db668c7 |
completed | April 5, 2026, 5:19 p.m. |
Created at: March 30, 2026, 8:29 p.m.