Triple
T20357956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baba Amr district |
E496699
|
entity |
| Predicate | peakOfSiege |
P139813
|
FINISHED |
| Object | early 2012 |
—
|
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: early 2012 | Statement: [Baba Amr district, peakOfSiege, early 2012]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakOfSiege Context triple: [Baba Amr district, peakOfSiege, early 2012]
-
A.
siegeRelated
Indicates a relationship in which one entity is involved with, associated with, or relevant to a siege or siege-related activities.
-
B.
isSiegeOf
Indicates a relationship where one event or action constitutes the military siege of a particular place, target, or entity.
-
C.
typeOfSiege
Indicates the specific kind or category of siege involved in a conflict or military operation.
-
D.
sieged
Indicates that one entity has surrounded and blockaded another entity or location, typically to cut off supplies and force surrender.
-
E.
siegeOccurredIn
Indicates that a siege took place within or at the location specified by the related entity.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67855c3a88190b88839a47d01184d |
completed | April 20, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69e57636b4808190bc2855af48a3ccdc |
completed | April 20, 2026, 12:41 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:25 a.m.