Triple
T8726754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alba Longa |
E207148
|
entity |
| Predicate | populationAfterDestruction |
P84294
|
FINISHED |
| Object | transferred to Rome |
—
|
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: transferred to Rome | Statement: [Alba Longa, populationAfterDestruction, transferred to Rome]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationAfterDestruction Context triple: [Alba Longa, populationAfterDestruction, transferred to Rome]
-
A.
populationLoss
Indicates a decrease in the number of individuals within a defined population over a given period or due to specific causes.
-
B.
areaDestroyed
Indicates that a specified portion or region has been damaged or ruined to the point of destruction.
-
C.
numberOfDistrictsDestroyed
Indicates the quantity of districts that have been destroyed in a given context or event.
-
D.
destroyedCity
Indicates that an entity has caused the complete or near-complete destruction of a city.
-
E.
buildingsDestroyed
Indicates that one or more buildings have been damaged to the point of destruction as a result of some event or action.
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d16cba881908e2a14b60ae65524 |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc489dd528819084ed5d88bd8bb3d6 |
completed | March 31, 2026, 10:20 p.m. |
Created at: March 30, 2026, 6:36 p.m.