Triple
T5828735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Métro Line 9 |
E129292
|
entity |
| Predicate | station |
P726
|
FINISHED |
| Object | Nation |
E65648
|
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: Nation | Statement: [Paris Métro Line 9, station, Nation]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nation Context triple: [Paris Métro Line 9, station, Nation]
-
A.
Nation
chosen
Nation is a major public square and transportation hub in eastern Paris, France, known for its large roundabout, prominent monuments, and busy metro and RER interchange.
-
B.
Nation
Nation is a common English surname shared by various individuals, including notable figures in entertainment and public life.
-
C.
National
National is a major centre-right political party in New Zealand, formally known as the New Zealand National Party.
-
D.
National
National is a Japanese electronics and home appliance brand historically used by Panasonic for a wide range of consumer products, especially in Asian markets.
-
E.
Nacional
Nacional is a news section of the Colombian newspaper El Espectador that focuses on national-level events and issues.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03467dfe48190b51757b33681bc20 |
completed | March 22, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c09863be3c8190bba357bf64e22917 |
completed | March 23, 2026, 1:33 a.m. |
Created at: March 22, 2026, 3:53 p.m.