Triple
T107761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1889 Exposition Universelle |
E2176
|
entity |
| Predicate | numberOfExhibitors |
P1131
|
FINISHED |
| Object | over 61,000 |
—
|
LITERAL 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: over 61,000 | Statement: [1889 Exposition Universelle, numberOfExhibitors, over 61,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfExhibitors Context triple: [1889 Exposition Universelle, numberOfExhibitors, over 61,000]
-
A.
numberOfParticipants
chosen
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
B.
usedByExhibitorType
Indicates that something is utilized or applied by a specific type or category of exhibitor.
-
C.
hasExhibition
Indicates that an entity organizes, hosts, or presents a particular exhibition.
-
D.
numberOfEvents
Indicates the quantity or count of events associated with a given entity or context.
-
E.
exhibitionType
Indicates the specific category or kind of exhibition associated with an entity (e.g., art show, trade fair, scientific exhibit).
- F. None of above.
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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25a1199ac8190ac65ffaaf45b4f5b |
completed | Feb. 28, 2026, 2:59 a.m. |
| PD | Predicate disambiguation | batch_69a2563e7188819091e9a94e071991d7 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.