Triple
T9487653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aquileia |
E228801
|
entity |
| Predicate | populationAtPeakApprox |
P3412
|
FINISHED |
| Object | 100000 |
—
|
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: 100000 | Statement: [Aquileia, populationAtPeakApprox, 100000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationAtPeakApprox Context triple: [Aquileia, populationAtPeakApprox, 100000]
-
A.
populationAtPeak
Indicates that an entity’s population size is measured at its highest recorded level during a specified time or condition.
-
B.
memberCountAtPeak
Indicates the highest number of members that an entity (such as a group or organization) has had at any point in time.
-
C.
hasPopulationAsOf
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
-
D.
hasPopulationApproximate
chosen
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
E.
numberOfEmployeesAtPeak
Indicates the highest recorded count of employees that an entity had at any point in time.
- 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_69ca847424f081908180305555139f7a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd80c443b88190968d2092a73e1ee4 |
completed | April 1, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69cca561e6b0819090aa795f3c3a2083 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:55 p.m.