Triple
T34735379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Qasioun |
E1001322
|
entity |
| Predicate | isAlsoSpelled |
P457
|
FINISHED |
| Object |
Jabal Qasioun
Jabal Qasioun is a prominent mountain overlooking Damascus, Syria, known for its strategic location, scenic views, and religious and historical significance.
|
E2110927
|
NE FINISHED |
How this triple was built (3 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: Jabal Qasioun | Statement: [Mount Qasioun, isAlsoSpelled, Jabal Qasioun]
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: Jabal Qasioun Triple: [Mount Qasioun, isAlsoSpelled, Jabal Qasioun]
Generated description
Jabal Qasioun is a prominent mountain overlooking Damascus, Syria, known for its strategic location, scenic views, and religious and historical significance.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAlsoSpelled Context triple: [Mount Qasioun, isAlsoSpelled, Jabal Qasioun]
-
A.
hasVariantSpelling
chosen
Indicates that one term is an alternative spelling form of another term.
-
B.
sharesSpellingWith
Indicates that two entities have identical or substantially identical written forms (i.e., they are spelled the same way).
-
C.
alsoWrittenAs
Indicates that one entity has an alternative written form, spelling, or notation represented by the other entity.
-
D.
spellingReplacedBy
Indicates that one spelling of a term has been superseded or substituted by another spelling.
-
E.
isSpokenAs
Indicates that one entity is used as the spoken or verbal form of another entity (e.g., a word, name, or phrase).
- F. None of above.
Provenance (6 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_69f76daf739881909ed3554f98a2b433 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3766286c8c8190ac3f5ed56aa065e5 |
completed | June 21, 2026, 4:18 a.m. |
| NEDg | Description generation | batch_6a3767e5df888190b19eb6b966f91c28 |
completed | June 21, 2026, 4:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3768467d608190b0287a796546281f |
completed | June 21, 2026, 4:27 a.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.