Triple
T15350926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lahab |
E367047
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Tabbat Yada |
E367046
|
NE 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: Tabbat Yada | Statement: [Lahab, alsoKnownAs, Tabbat Yada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tabbat Yada Context triple: [Lahab, alsoKnownAs, Tabbat Yada]
-
A.
Tabbat Yada
chosen
Tabbat Yada is a short Meccan Qur’anic chapter that condemns Abu Lahab and serves as a warning against opposition to the Prophet Muhammad.
-
B.
Yebba
Yebba is an American singer-songwriter known for her powerful, soulful vocals and emotionally rich R&B and soul-influenced music.
-
C.
Jellaby
Jellaby is a minor but memorable character in Tom Stoppard’s play "Arcadia," serving as the butler whose presence adds humor and helps frame the household’s social world.
-
D.
Jellaby
Jellaby is a gentle, dragon-like creature from the all-ages fantasy comic series "Jellaby" by Kean Soo, where it befriends a lonely girl and accompanies her on mysterious adventures.
-
E.
El Tebbin
El Tebbin is an industrial district in southern Cairo, Egypt, known for its steel and heavy manufacturing facilities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e290efc8190b22c95dcd3e5f57f |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1341033881909121ade33cecaf50 |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:17 a.m.