Triple
T7001675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helvetii |
E162350
|
entity |
| Predicate | estimatedTotalMigrants |
P17800
|
FINISHED |
| Object | about 368,000 according to Caesar |
—
|
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: about 368,000 according to Caesar | Statement: [Helvetii, estimatedTotalMigrants, about 368,000 according to Caesar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedTotalMigrants Context triple: [Helvetii, estimatedTotalMigrants, about 368,000 according to Caesar]
-
A.
estimatedEmigrants
chosen
Indicates the estimated number of people who have left a place or country to live elsewhere.
-
B.
numberOfImmigrantsProcessed
Indicates the total count of immigrants that have been processed in a given context or system.
-
C.
immigrantPopulationShare
Indicates the proportion of a total population that is made up of immigrants.
-
D.
hasSignificantEmigrationTo
Indicates that a substantial number of people leave one place, group, or entity to move and settle in another specific place, group, or entity.
-
E.
estimatedNumberOfPeopleDeported
Indicates the approximate count of individuals who were forcibly removed or expelled from a place or country.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc0f8830819091f4356296234713 |
completed | March 27, 2026, 7:35 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c67c94819084fdcf0398606027 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:33 p.m.