Triple
T15454587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thermidor |
E371736
|
entity |
| Predicate | follows |
P134
|
FINISHED |
| Object | Messidor |
E371735
|
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: Messidor | Statement: [Thermidor, follows, Messidor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Messidor Context triple: [Thermidor, follows, Messidor]
-
A.
Messidor
chosen
Messidor is the tenth month of the French Republican Calendar, corresponding roughly to late June and most of July, whose name evokes the harvest.
-
B.
Picquart
Picquart is a French surname most notably associated with Georges Picquart, the army officer who exposed the wrongful conviction of Alfred Dreyfus.
-
C.
Boizel
Boizel is a historic Champagne producer renowned for its elegant, terroir-driven sparkling wines crafted in Épernay, France.
-
D.
Charroux
Charroux is a historic commune in western France known for its medieval heritage and the remains of its once-prominent Benedictine abbey.
-
E.
Oberkampf
Oberkampf is a Paris Métro station in the 11th arrondissement, serving as an interchange between lines 5 and 9 near the lively Oberkampf district.
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f131b1481909ff099c3b844ee07 |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21b5e1788190bdc8182822f25fa1 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:31 a.m.