Triple
T34734168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Congo Square |
E1001290
|
entity |
| Predicate | hasNameInPast |
P199075
|
FINISHED |
| Object | Place des Nègres |
—
|
NE NERFINISHED |
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: Place des Nègres | Statement: [Congo Square, hasNameInPast, Place des Nègres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameInPast Context triple: [Congo Square, hasNameInPast, Place des Nègres]
-
A.
usedInPastBy
Indicates that an entity was previously utilized or employed by another entity at some time in the past.
-
B.
usedInPast
Indicates that an entity has been utilized or employed at some point in the past, prior to the current time or context.
-
C.
usedInPastFor
Indicates that one entity was previously utilized for another entity or purpose in the past.
-
D.
hasPastTenseEnding
Indicates that a verb form ends with a morphological marker typically used to express past tense.
-
E.
hasComplexPast
Indicates that an entity has a history characterized by multiple significant, intricate, or difficult events or circumstances.
- F. None of above. chosen
Provenance (4 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_69f76daf739881909ed3554f98a2b433 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69ff1d85441c8190931e758685a269f7 |
completed | May 9, 2026, 11:41 a.m. |
| PD | Predicate disambiguation | batch_69ff1d186cc48190b315c61e23de6551 |
completed | May 9, 2026, 11:40 a.m. |
| PDg | Predicate description generation | batch_69ff1d8394988190acf163a07acad200 |
completed | May 9, 2026, 11:41 a.m. |
Created at: May 3, 2026, 3:59 p.m.