Triple
T13292463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rif Dimashq Governorate |
E316591
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Qatana
Qatana is a town in southwestern Syria that serves as an administrative center and lies near the capital, Damascus.
|
E1033427
|
NE FINISHED |
How this triple was built (4 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: Qatana | Statement: [Rif Dimashq Governorate, contains, Qatana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Qatana Context triple: [Rif Dimashq Governorate, contains, Qatana]
-
A.
Talwara
Talwara is a small town in the Indian state of Himachal Pradesh, known primarily for its proximity to the Pong Dam on the Beas River.
-
B.
Orpo
Orpo was the uniformed regular police force of Nazi Germany, responsible for maintaining public order and involved in numerous wartime atrocities and repressive activities.
-
C.
The Spear
The Spear is the nickname of the U.S. Air Force’s 53rd Wing, a unit known for operational testing and evaluation of advanced weapons and systems.
-
D.
Machetá
Machetá is a municipality and town in the Cundinamarca Department of Colombia, located in the Andean highlands northeast of Bogotá.
-
E.
The Weapon
The Weapon is a film featuring American actor Steve Cochran, known for his tough-guy roles in mid-20th-century crime and drama movies.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Qatana Triple: [Rif Dimashq Governorate, contains, Qatana]
Generated description
Qatana is a town in southwestern Syria that serves as an administrative center and lies near the capital, Damascus.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Qatana Target entity description: Qatana is a town in southwestern Syria that serves as an administrative center and lies near the capital, Damascus.
-
A.
Talwara
Talwara is a small town in the Indian state of Himachal Pradesh, known primarily for its proximity to the Pong Dam on the Beas River.
-
B.
Orpo
Orpo was the uniformed regular police force of Nazi Germany, responsible for maintaining public order and involved in numerous wartime atrocities and repressive activities.
-
C.
The Spear
The Spear is the nickname of the U.S. Air Force’s 53rd Wing, a unit known for operational testing and evaluation of advanced weapons and systems.
-
D.
Machetá
Machetá is a municipality and town in the Cundinamarca Department of Colombia, located in the Andean highlands northeast of Bogotá.
-
E.
The Weapon
The Weapon is a film featuring American actor Steve Cochran, known for his tough-guy roles in mid-20th-century crime and drama movies.
- F. None of above. chosen
Provenance (5 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99078bcf0819083195fb556bcacb2 |
completed | April 11, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716d6dc988190ab7183089113237f |
completed | May 3, 2026, 9:35 a.m. |
| NEDg | Description generation | batch_69f717f4d80c8190a1a95c0f2c83c563 |
completed | May 3, 2026, 9:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f718b852808190a2a0fb48424bffb0 |
completed | May 3, 2026, 9:43 a.m. |
Created at: April 9, 2026, 9:27 p.m.