Triple
T18453089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Damascus Eyalet |
E450835
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Lajjun
Lajjun was a historical town and administrative center in the Levant, known for its strategic location and role in regional governance during the Ottoman period.
|
E1325854
|
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: Lajjun | Statement: [Damascus Eyalet, contains, Lajjun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lajjun Context triple: [Damascus Eyalet, contains, Lajjun]
-
A.
Lafiya
Lafiya is a town associated with the Bachama people in Nigeria, serving as one of their local settlements.
-
B.
Laja
Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
-
C.
Lahej
Lahej was a former sultanate in southern Arabia that later became part of the British-influenced Federation of South Arabian states.
-
D.
Larhat
Larhat is a coastal town and commune in northern Algeria, situated within Tipaza Province along the Mediterranean Sea.
-
E.
Molazzana
Molazzana is a small municipality in Tuscany, central Italy, known for its scenic location in the Garfagnana area of the Apennine mountains.
- 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: Lajjun Triple: [Damascus Eyalet, contains, Lajjun]
Generated description
Lajjun was a historical town and administrative center in the Levant, known for its strategic location and role in regional governance during the Ottoman period.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lajjun Target entity description: Lajjun was a historical town and administrative center in the Levant, known for its strategic location and role in regional governance during the Ottoman period.
-
A.
Lafiya
Lafiya is a town associated with the Bachama people in Nigeria, serving as one of their local settlements.
-
B.
Laja
Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
-
C.
Lahej
Lahej was a former sultanate in southern Arabia that later became part of the British-influenced Federation of South Arabian states.
-
D.
Larhat
Larhat is a coastal town and commune in northern Algeria, situated within Tipaza Province along the Mediterranean Sea.
-
E.
Molazzana
Molazzana is a small municipality in Tuscany, central Italy, known for its scenic location in the Garfagnana area of the Apennine mountains.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5264a49ec8190aa43381d93a55e91 |
completed | April 19, 2026, 7 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a040fe5eb1081909ecdf53f4b6b9370 |
completed | May 13, 2026, 5:45 a.m. |
| NEDg | Description generation | batch_6a043a81cd58819089df50804870952e |
completed | May 13, 2026, 8:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a043c0580048190afd9fe46e6863918 |
completed | May 13, 2026, 8:53 a.m. |
Created at: April 10, 2026, 11:31 a.m.