Triple
T7304432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byblos Castle |
E167938
|
entity |
| Predicate | hasLayeredHistory |
P58089
|
FINISHED |
| Object | Phoenician period remains |
—
|
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: Phoenician period remains | Statement: [Byblos Castle, hasLayeredHistory, Phoenician period remains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLayeredHistory Context triple: [Byblos Castle, hasLayeredHistory, Phoenician period remains]
-
A.
hasHistoricalSuperstrate
Indicates that one language or culture has served as a historically dominant external influence shaping another language or culture, typically through contact, conquest, or prestige.
-
B.
hasHistorySince
Indicates that an entity has maintained a particular state, condition, or relationship continuously starting from a specified point in time.
-
C.
hasHistoryPeriod
chosen
Indicates that something is associated with, belongs to, or occurs within a specific historical period or era.
-
D.
hasTypeHistory
Indicates that an entity is associated with a record or sequence of its past and present types or classifications over time.
-
E.
hasScriptHistory
Indicates that an entity is associated with a record or chronology of scripts or writing systems it has used or been represented in over time.
- 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_69c6888c820881909fc68f689fe1c251 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebb352ec8190846eff044e08805e |
completed | March 27, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69c6e76e67d88190bd3ca6864f45845a |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:01 p.m.