Triple
T3879120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Ramadi |
E92576
|
entity |
| Predicate | hasSecurityHistory |
P37550
|
FINISHED |
| Object | experienced insurgency-related violence after 2003 |
—
|
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: experienced insurgency-related violence after 2003 | Statement: [Al-Ramadi, hasSecurityHistory, experienced insurgency-related violence after 2003]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecurityHistory Context triple: [Al-Ramadi, hasSecurityHistory, experienced insurgency-related violence after 2003]
-
A.
hasAccessRestrictionHistory
Indicates that there exists a record or sequence of past changes detailing how access to something has been restricted over time.
-
B.
hasPolicyHistory
Indicates that an entity is associated with a record or sequence of past policies that have applied to it over time.
-
C.
hasFireHistory
Indicates that an entity has experienced one or more fire events in the past.
-
D.
hasHistoryOf
chosen
Indicates that an entity has a documented prior occurrence or background of a specified condition, event, or state.
-
E.
hasTransportHistoryAs
Indicates that an entity has a record or log of being transported, characterized or classified in a specific way.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.