Triple
T11698867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahalwari system |
E278067
|
entity |
| Predicate | collectionResponsibility |
P87654
|
FINISHED |
| Object |
lambardars
Lambardars were village-level revenue officials in colonial India responsible for collecting land taxes and maintaining order on behalf of the state.
|
E939699
|
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: lambardars | Statement: [Mahalwari system, collectionResponsibility, lambardars]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: lambardars Context triple: [Mahalwari system, collectionResponsibility, lambardars]
-
A.
laamb
Laamb is a traditional form of Senegalese wrestling that combines physical combat with cultural rituals, music, and community celebration.
-
B.
Lamerd
Lamerd is a city in southern Iran known for its hot desert climate and role as a regional center within Fars Province.
-
C.
Lamlash
Lamlash is a coastal village and the largest settlement on the Isle of Arran in Scotland, known for its scenic bay facing Holy Isle.
-
D.
L.A.M.B.
L.A.M.B. is Gwen Stefani’s fashion label known for its bold, eclectic designs that blend punk, streetwear, and high-fashion influences.
-
E.
Lamalerans
Lamalerans are an indigenous ethnic group from Lembata Island in Indonesia, renowned for their traditional subsistence whaling and seafaring culture.
- 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: lambardars Triple: [Mahalwari system, collectionResponsibility, lambardars]
Generated description
Lambardars were village-level revenue officials in colonial India responsible for collecting land taxes and maintaining order on behalf of the state.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: lambardars Target entity description: Lambardars were village-level revenue officials in colonial India responsible for collecting land taxes and maintaining order on behalf of the state.
-
A.
laamb
Laamb is a traditional form of Senegalese wrestling that combines physical combat with cultural rituals, music, and community celebration.
-
B.
Lamerd
Lamerd is a city in southern Iran known for its hot desert climate and role as a regional center within Fars Province.
-
C.
Lamlash
Lamlash is a coastal village and the largest settlement on the Isle of Arran in Scotland, known for its scenic bay facing Holy Isle.
-
D.
L.A.M.B.
L.A.M.B. is Gwen Stefani’s fashion label known for its bold, eclectic designs that blend punk, streetwear, and high-fashion influences.
-
E.
Lamalerans
Lamalerans are an indigenous ethnic group from Lembata Island in Indonesia, renowned for their traditional subsistence whaling and seafaring culture.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a47df68c81908a91919a69b4880d |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef147e2e10819085eaed83fd955b6b |
completed | April 27, 2026, 7:47 a.m. |
| NEDg | Description generation | batch_69ef3553a1748190b554463bcea8bd1d |
completed | April 27, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ef51fe3824819099f440426d3e6888 |
completed | April 27, 2026, 12:09 p.m. |
Created at: April 8, 2026, 9:40 p.m.